U.S. patent application number 16/028478 was filed with the patent office on 2019-01-10 for preference visualization system and censorship system.
This patent application is currently assigned to UNIVERSAL ENTERTAINMENT CORPORATION. The applicant listed for this patent is UNIVERSAL ENTERTAINMENT CORPORATION. Invention is credited to Jun FUJIMOTO, Hiroshi KATSUKURA, Nobuyuki NONAKA.
Application Number | 20190012376 16/028478 |
Document ID | / |
Family ID | 46969178 |
Filed Date | 2019-01-10 |
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United States Patent
Application |
20190012376 |
Kind Code |
A1 |
FUJIMOTO; Jun ; et
al. |
January 10, 2019 |
PREFERENCE VISUALIZATION SYSTEM AND CENSORSHIP SYSTEM
Abstract
A censorship system and method that receives monitored
user-generated data, decomposes the monitored data into related
terminology, extracts, from the related terminology, a
characteristic of the received monitored data, determines a
preference of the individual person to be monitored for a specific
object based on the extracted characteristic, determines, based on
the determined preference for the specific object, whether (i)
blocking or terminating of information provision, or (ii) execution
of new information provision appropriate to the determined
preference, would be an appropriate censorship control command for
the individual person to be monitored for the specific object, and
outputs an appropriate censorship control command for the
individual person for the specific object.
Inventors: |
FUJIMOTO; Jun; (Tokyo,
JP) ; NONAKA; Nobuyuki; (Tokyo, JP) ;
KATSUKURA; Hiroshi; (Tokyo, JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
UNIVERSAL ENTERTAINMENT CORPORATION |
Tokyo |
|
JP |
|
|
Assignee: |
UNIVERSAL ENTERTAINMENT
CORPORATION
Tokyo
JP
|
Family ID: |
46969178 |
Appl. No.: |
16/028478 |
Filed: |
July 6, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14006217 |
Sep 19, 2013 |
10055487 |
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PCT/JP2012/059093 |
Apr 3, 2012 |
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16028478 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/335
20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Foreign Application Data
Date |
Code |
Application Number |
Apr 8, 2011 |
JP |
2011-086407 |
Claims
1. A censorship system, comprising: one or more processors
programmed to: receive monitored data that is generated by an
individual person to be monitored who is a censor object; decompose
the monitored data into related terminology, which is a plurality
of units capable of identifying a meaning; extract, from the
related terminology, a characteristic of the received monitored
data based on the plurality of units capable of identifying the
meaning; determine a preference of the individual person for a
specific object based on the extracted characteristic; determine,
based on the determined preference, whether (i) blocking or
terminating of information provision, or (ii) execution of new
information provision appropriate to the determined preference,
would be an appropriate censorship control command for the
individual person for the specific object; and output a censorship
control command for the individual person for the specific object
that is a censorship control command of a type that is the same as
the type of the determined appropriate censorship control command
for the individual person for the specific object.
2. A censorship system, comprising: one or more processors
programmed to: receive monitored text data that is composed of a
plurality of character strings generated by an individual person to
be monitored who is a censor object; abstract any personal
information by which an individual person can be directly
identified from the received monitored text data; decompose the
remaining monitored text data after abstraction into related
terminology, which is a plurality of units that are capable of
identifying a meaning and that includes at least one of the
following types of categories: a genre, a preference, a dialect and
a feeling; extract, from the related terminology, a characteristic
of the received monitored data based on the plurality of units
capable of identifying the meaning; determine a preference of the
individual person for a specific object based on the extracted
characteristic; determine, based on the determined preference,
whether (i) blocking or terminating of information provision or
(ii) execution of new information provision service appropriate to
the determined preference, would be an appropriate censorship
control command for the individual person for the specific object;
and output a censorship control command for the individual person
for the specific object that is a censorship control command of a
type that is the same as the type of the determined appropriate
censorship control command for the individual person for the
specific object, wherein the outputted censorship control command
is a specific executable command for the individual person based on
the determined preference, and the outputted censorship control
command causes blocking of information containing a particular
expression.
3. A method comprising: receiving, by one or more processors,
monitored text data composed of a plurality of character strings
that are generated by an individual person to be monitored who is a
censor object; abstracting, by the one or more processors, any
personal information by which an individual person can be directly
identified from the received monitored text data; decomposing, by
the one or more processors, the remaining text data after
abstraction into related terminology, which is a plurality of units
capable of identifying a meaning; extracting, by the one or more
processors, from the related terminology, a characteristic of the
received monitored text data based on the plurality of units
capable of identifying the meaning; determining, by the one or more
processors, a preference of the individual person for a specific
object based on the extracted characteristic; determining, by the
one or more processors, based on the determined preference, whether
(i) blocking or terminating of information provision or (ii)
execution of new information provision appropriate to the
determined preference, would be an appropriate censorship control
command for the individual person for the specific object; and
outputting, by the one or more processors, a censorship control
command for the individual person for the specific object that is a
censorship control command of a type that is the same as the type
of the determined appropriate censorship control command for the
individual person for the specific object.
4. A method comprising: receiving, by one or more processors, text
data composed of a plurality of character strings generated by an
individual person to be monitored who is a censor object;
decomposing, by the one or more processors, the received text data
into related terminology, which is a plurality of units capable of
identifying the meaning; extracting, by the one or more processors,
from the related terminology, related text data from the decomposed
text data that both satisfies: (i) a predetermined relation
condition regarding a specific object indicated by the decomposed
text data, and (ii) a predetermined characteristic condition based
on an attribute that corresponds to a preference of the individual
person; determining, by the one or more processors, based on the
related text data satisfying the predetermined conditions, whether
(i) blocking or terminating of information provision or (ii)
execution of new information provision appropriate to the
preference of the individual person, would be an appropriate
censorship control command for the individual person for the
specific object; and outputting, by the one or more processors, a
censorship control command for the individual person for the
specific object that is a censorship control command of a type that
is the same as the type of the determined appropriate censorship
control command for the individual person for the specific object,
wherein the predetermined relation condition includes one or more
accompanying terms associated with the object.
5. A method comprising: receiving, by one or more processors, text
data composed of a plurality of character strings that are
generated by an individual person to be monitored who is a censor
object; decomposing, by the one or more processors, the individual
person generated text data into related terminology, which is a
plurality of units capable of identifying the meaning; extracting,
by the one or more processors, from the related terminology, a
characteristic of the received text data based on the plurality of
units capable of identifying the meaning; determining, by the one
or more processors, a preference of the individual person for a
specific object based on the extracted characteristic; determining,
by the one or more processors, based on the determined preference,
whether (i) blocking or terminating of information provision or
(ii) execution of new information provision appropriate to the
determined preference, would be an appropriate censorship control
command for the individual person for the specific object; and
outputting, by the one or more processors, a censorship control
command for the individual person for the specific object that is a
censorship control command of a type that is the same as the type
of the determined appropriate censorship control command for the
individual person for the specific object.
6. A method comprising: receiving, by one or more processors, text
data composed of a plurality of character strings that are
generated by an individual person to be monitored who is a censor
object; decomposing, by the one or more processors, the individual
person generated text data into related terminology, which is
decomposed text data capable of identifying the meaning;
extracting, by the one or more processors, from the related
terminology, a characteristic of the received text data;
determining, by the one or more processors, a preference of the
individual person for a specific object based on the extracted
characteristic; determining, by the one or more processors, based
on the determined preference, whether (i) blocking or terminating
of information provision or (ii) execution of new information
provision appropriate to the determined preference, would be an
appropriate censorship control command for the individual person
for the specific object; and outputting, by the one or more
processors, a censorship control command for the individual person
for the specific object that is a censorship control command of a
type that is the same as the type of the determined appropriate
censorship control command for the individual person for the
specific object, wherein the censorship control command causes the
execution of new information provision appropriate to the
determined preference.
Description
TECHNICAL FIELD
[0001] The present invention relates to a system which monitors
text acquired via a network.
BACKGROUND ART
[0002] Conventionally, there has been a method and a device which
block the provision of information that is determined to be
inappropriate out of information provided via a network (for
example, refer to Patent Document 1). Such method and device is for
preventing children and the like from visibly recognizing
information that is determined to be harmful out of information
provided via a network. It has been determined whether or not the
term should be blocked by extracting terms from information
provided via a network and reading out significance to each of the
extracted terms from a term list previously determined and
stored.
PRIOR ART DOCUMENT
Patent Document
[0003] [Patent Document 1] Japanese Patent Application Laid-open
No. 2001-28006
SUMMARY OF THE INVENTION
Problems to be Solved by the Invention
[0004] Although a conventional censorship system is effective for
information in which a term to be inappropriate clearly appears, it
has been incompetent to information which is transmitted after
being subject to repression and deformation in a field of
censorship. Here, the field of censorship is a space composed of a
collection of text that is to be an object to be censored provided
by a user.
[0005] Therefore, in a conventional main system which provides
information service, no approach has been established to handle
information which is transmitted after being subject to repression
and deformation in the field of censorship formed for each
community in which users of the main system participate, and thus
such information has been often left untreated.
[0006] For example, in the case where the above-mentioned main
system is an artificial intelligence system which answers questions
from users, preference information present in the field of
censorship is left untreated, and only answers to the question are
given while lacking of a censoring function in the field of
censorship.
[0007] In light of foregoing, the present invention is made and the
purpose thereof is to provide an information processing system
capable of properly addressing information, such as preference
information, which is transmitted after being subject to repression
and deformation in the field of censorship, or to provide an
information availability system for the information concerned and
an information availability function for the information concerned
which are necessary to achieve the information processing
system.
Means for Solving the Problems
[0008] An information processing system according to the present
embodiment is provided with:
[0009] a field-of-censorship generation device for decomposing
individual person generated data generated by an individual person
into a plurality of decomposed data that can identify the meaning,
extracting data that satisfies both a predetermined relation
condition regarding an object indicated by each of the decomposed
data and a predetermined characteristic condition regarding the
object, and generating a collection of first extracted data
extracted thereby as a field of censorship; and
[0010] a device for making particularity available for extracting
data that satisfies a particular condition indicating a
predetermined particularity in connection with the object from the
collection of the first extracted data, and detecting the
predetermined particularity from second extracted data extracted
thereby to make it available.
Effects of the Invention
[0011] It is possible to properly address information which is
transmitted after being subject to repression and deformation in
the field of censorship.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] FIG. 1A is a block diagram showing an overview of a main
system using a information availability system and a censorship
system according to the present embodiment, and FIG. 1B is a block
diagram showing an overview of the preference availability
system.
[0013] FIGS. 2A-2F are block diagrams showing overviews of
processing in the preference availability system and the censorship
system according to various embodiments.
[0014] FIG. 3A is a diagram showing an overview of a field of
censorship in the preference availability system and the censorship
system according to the present embodiment, and FIG. 3B is a
diagram showing time change in the field of censorship.
[0015] FIG. 4 is a diagram showing an example of a network to which
the preference availability system (the censorship system) of the
present embodiment is connected.
[0016] FIG. 5 is a block diagram showing an overview of the
preference availability system and the censorship system according
to the present embodiment.
[0017] FIG. 6 is a block diagram showing an overview of a partial
space generation device in the preference availability system and
the censorship system according to the present embodiment.
[0018] FIG. 7 is a block diagram showing an overview of a candidate
space generation device in the preference availability system and
the censorship system according to the present embodiment.
[0019] FIG. 8 is a block diagram showing an overview of a
monitoring space generation device in the preference availability
system and the censorship system according to the present
embodiment.
[0020] FIG. 9 is a block diagram showing an overview of a
historical space generation device in the preference availability
system and the censorship system according to the present
embodiment.
[0021] FIG. 10 is a block diagram showing an overview of a
preference availability system (censorship system) available
online.
[0022] FIG. 11 is a block diagram showing an overview of a partial
space generation device in a preference availability system
(censorship system) available online.
[0023] FIG. 12 is a block diagram showing an overview of a
monitoring device in a preference availability system and a
censorship system according to the present embodiment.
[0024] FIG. 13 is a block diagram showing an overview of a
censorship control device in a preference availability system and a
censorship system according to the present embodiment.
[0025] FIG. 14 is a block diagram showing a preference availability
system and a censorship system according to a first working
example.
[0026] FIG. 15 is a block diagram showing a preference availability
system and a censorship system according to a second working
example.
[0027] FIG. 16 is a block diagram showing a preference availability
system and a censorship system according to a third working
example.
MODE FOR CARRYING OUT THE INVENTION
[0028] Embodiments of the present invention will be described below
based on drawings.
[0029] <<Overview of the Present Embodiment>>
[0030] FIG. 1(a) is a block diagram showing an overview of a main
system using a information availability system and a censorship
system according to the present embodiment.
[0031] A customer (an individual person) of a main system inputs a
variety of text data by an entry box on the web screen, e-mail,
blog, a bulletin board, Twitter, and the like. This is a
transmission of information of the individual person. Such text
data is acquired by the main system. In general, the transmission
of information by the individual person is stored in a server of
the main system as text data in a state where it can be read via a
network.
[0032] The main system is the system which offers service mainly
such as an EC site, SNS, a search site, an artificial intelligence
site, etc. The main system provides a customer of the main system
with individual service (main service) in accordance with the main
system. In addition, the EC site is the site which mainly offers a
company's own products and services utilizing a network.
Furthermore, SNS is the service mainly for forming a social network
using a variety of networks in order to encourage a
person-to-person communication. The search site is the site which
mainly offers service for searching a web site of interest in order
to acquire a variety of information. Furthermore, the artificial
intelligence is the site which is configured to offer service
capable of having an automatic conversation via a network.
[0033] The main system has a database which stores personal
information on a customer of the main system. The personal
information is the information on a customer, such as real name and
address of the customer, which is necessary for the service offered
by the main system.
[0034] The main system supplies the transmission of information
acquired from the customer to a censorship system. The censorship
system has a database for executing a variety of censorship
controls. The censorship system generates a field of censorship,
and provides a censorship control (individual service) suitable for
the main system with reference to a database for the censorship
control, as described below. For example, when it is determined
that a customer is interested in a new product, a variety of
information on the new product is provided for him/her.
Furthermore, information, music, moving images or the like which
gives a peace of mind is provided for a customer who bears a
psychological or mental burden. Furthermore, if a person transmits
antisocialistic information and information counter to common
sense, a variety of services can be suspended, such as termination
of the network connection
[0035] The censorship system supplies information for censoring
regarding the transmission of information acquired from the
customer to a information availability system. The information
availability system accumulates historical information out of the
supplied information for censoring, and also generates monitoring
information from the historical information to supply it to the
censorship system. The censorship system provides the main system
with the censorship control (individual service) described above
based on the supplied monitoring information.
[0036] FIG. 1(b) is a block diagram showing an overview of the
information availability system according to the present
embodiment. The information availability system is composed of a
field-of-censorship generation function, a information availability
function, and a monitoring function. The field-of-censorship
generation function is the function for detecting a particularity
regarding the transmitted information from the generated field of
censorship so as to make the particularity available. The
monitoring function is the function for monitoring mainly an
individual person who has transmitted information, with regard to
the transmitted information from which the particularity is
detected.
[0037] FIGS. 2A and 2B are block diagrams showing an overview of a
preference availability system and a censorship system according to
the present embodiment.
[0038] <<First Aspect>>
[0039] According to a first aspect of the present embodiment, a
system includes a computer for receiving single external
information containing text data composed of a plurality of
character strings and executing a program that extracts information
particular to the contents thereof, the computer executing the
program so as to execute the procedures of:
[0040] abstracting input text data to convert it into a plurality
of related text data that is previously prepared;
[0041] determining related data as particular related text data if
a particular condition indicating a predetermined particularity
regarding an object indicated by the related text data is satisfied
with regard to the one external information; and
[0042] storing the related text data determined as the particular
related text data in connection with the condition regarding a user
ID contained in the external information for identifying an
individual person and the condition regarding the particular
condition.
[0043] For example, a new preference extraction function is
provided which captures an expression frequently appeared in a
conversation of a particular individual person as a particular one.
This makes it possible to indirectly determine food and hobbies
which the individual person likes, or a genre which the individual
person is interested in.
[0044] <<Second Aspect>>
[0045] Furthermore, according to a second aspect of the present
embodiment, it is included the steps of:
[0046] abstracting data containing predetermined contents from text
data based on individual person generated data generated by an
individual person, and decomposing the abstracted text data into
decomposed text data that can identify the meaning; and
[0047] storing the decomposed text data in connection with a user
ID that can identify the individual person who has generated the
individual person generated data.
[0048] A second aspect of the present embodiment will be described
with reference to FIG. 2A. First, data containing a predetermined
kind of contents is abstracted from text data based on an
individual generated data generated by an individual person. In the
present embodiment, the individual generated data is just has to be
data generated by an individual person, including text data which
is input by an individual person by means of a keyboard, for
example. This kind of text data includes text data input in an
input box on a web screen, e-mail, blog, a bulletin board, Twitter
(Registered Trademark), etc. Furthermore, the data generated by an
individual person also includes voice data, image data, etc. In
case of the voice data and the image data, executing recognition
processing can convert the data into text data. The text data based
on the individual person generated data generated by an individual
person means the text data which is converted from the voice data,
the image data and the like in this way.
[0049] Furthermore, a predetermined kind of contents includes
personal information, for example. Here, the personal information
refers to the information such as name, address, telephone number
and the like by which an individual person can be directly
identified. In addition, although an account and a handle name may
identify an individual person by referring to other databases and
the like, the individual person itself cannot be identified
directly by the information itself, and thus they are not regarded
as the personal information. In this way, abstracting a
predetermined kind of contents makes it possible to prevent the
predetermined kind of contents such as the personal information
from being contained in the text data to be processed.
[0050] Furthermore, the text data in which the predetermined kind
of contents is abstracted is decomposed into decomposed text data
capable of identifying the meaning. For example, the processing for
decomposing data into the decomposed text data capable of
identifying the meaning includes the morphological analysis, etc.
The morphological analysis can separate the text data into
predetermined parts of speech such as noun, verb, and adjective,
and into unit data that can identify the meaning.
[0051] Yet further, the decomposed text data is stored in
connection with an user ID. Here, the user ID is information by
which an individual person who has generated individual person
generated data can be identified. In addition, the information is
just has to be one that can identify an individual person, and thus
it necessarily has to be one for identifying personal
information.
[0052] This provides the abstraction of data containing a
predetermined kind of contents, so that it is possible to prevent
the data indicating a predetermined kind of contents contained in
the individual person generated data, such as personal information,
from leaking out of the preference availability system and the
censorship system to the outside.
[0053] The decomposed text data corresponds to a "related
term".
[0054] <<Third Aspect>>
[0055] Furthermore, according to a third aspect of the present
embodiment, it is included the steps of:
[0056] decomposing text data based on individual person generated
data generated by an individual person into decomposed text data
that can identify the meaning, and extracting related text data
indicating a related object that satisfies a predetermined relation
condition regarding a predetermined object indicated by the
decomposed text data out of the decomposed text data; and
[0057] storing the related text data in connection with the
predetermined relation condition.
[0058] A third aspect of the present embodiment will be described
with reference to FIG. 2B. First, a related text data indicating a
related object is extracted from the decomposed data. The
decomposed text data is unit data in which the text data is divided
so as to be able to identify the meaning, as described above.
[0059] The related object is the object that satisfies a
predetermined relation condition regarding an object indicated by
the decomposed text data. A predetermined object indicated by the
decomposed text data is a variety of topics and contents contained
in text data such as e-mail. Specifically, a predetermined kind of
food, car, and tourist destination are included. The relation
satisfies a predetermined relation condition. For example, when a
predetermined object is ramen noodle as food, a predetermined
relation condition is defined so that the related object can
include ramen noodle with soup flavored with soy source, salt, pork
bone broth, etc.
[0060] Such predetermined object and relation condition can be
defined so that information that an operator of the censorship
system desires can be extracted. When only the predetermined object
is extracted, the related object cannot be extracted, and thus the
extraction result may be insufficient. The relation condition is
appropriately defined, so that it is possible to extract not only
the predetermined object, but also information containing both the
predetermined object and the related object in relation thereof. An
operator of the censorship system defines the relation condition,
so that it is possible to extract the desired information
adequately, i.e., not so broadly and narrowly.
[0061] A step of extracting the related text data indicating the
related object which satisfies the predetermined relation condition
corresponds to a "basic filter." One relation condition corresponds
to one basic filter. The step of extracting a related text data
from a decomposed text data by one relation condition generates one
domain. One domain includes both the decomposed text data
indicating a predetermined object, and the decomposed text data
indicating a related object. The related text data is composed of
the decomposed text data indicating a predetermined object, and the
decomposed text data indicating a related object.
[0062] The domain means a collection which is composed of the
related text data extracted from the decomposed text data. Making
the relation condition different generates a single domain in
accordance with that relation condition. The operator of the
censorship system can define the relation condition. Therefore, the
operator of the censorship system can define a plurality of
relation condition so as to be able to acquire a desired extracted
result, and generate a domain for each thereof.
[0063] As shown in FIG. 3A, the domain for indicating the relation
condition described above is configured. The domain is for
classifying and identifying a plurality of relation conditions.
Therefore, the domain is generated corresponding to each of a
plurality of relation conditions.
[0064] The example of the field of censorship shown in FIG. 3A
represents only four domains, namely u.sub.1 to u.sub.4. As
described above, making the relation condition (the basic filter)
different generates four domains (u.sub.1 to u.sub.4). In FIG. 3A,
each of four domains is indicated by in a surrounding broken line.
As mentioned below, each of four domains (u.sub.1 to u.sub.4) is
composed of five partial spaces. The domains shown in FIG. 3A
represent the example in the figure in which four domains (u.sub.1
to u.sub.4) are generated using four relation conditions (basic
filters). The related text data satisfying the relation condition
belongs to each of the domains, the relation condition
corresponding to each of the domains.
[0065] Furthermore, the extracted related text data is stored in
connection with a predetermined relation condition. This makes it
possible to store not only the related text data but also the
predetermined relation condition by which the the related text data
is extracted, and thus the condition of the following processing
can be appropriately defined. Specifically, not only a single term
in information that a predetermined individual person has been
transmitted is regarded as an object of the censorship, but also
terms in relation to a single term included in the transmitted
information, for example slang, can be included. The region to be
censored can be broadened.
[0066] <<Fourth Aspect>>
[0067] Furthermore, according to a fourth aspect of the present
invention, it is included the steps of:
[0068] extracting characteristic text data that satisfies a
predetermined characteristic condition regarding an attribute of an
object indicated by text data out of the text data based on
individual person generated data generated by an individual person;
and
[0069] storing the characteristic text data in connection with the
predetermined characteristic condition.
[0070] A fourth aspect of the present embodiment will be described
with reference to FIG. 2C. First, a characteristic text data that
satisfies a predetermined characteristic condition is extracted
from text data. The predetermined characteristic condition is a
condition regarding an attribute of a predetermined object
indicated by the text data. The attribute is a variety of
characteristics of the predetermined object, such as a property and
a feature. The variety of characteristics may be not only an
objective characteristic, but also a characteristic which is
subjectively expressed based on feelings and emotion regarding the
predetermined object.
[0071] Furthermore, the attribute can be regarded as so-called
preference. An emotional characteristic regarding a predetermined
object and a statistical characteristic regarding a predetermined
object are included. The emotional characteristic includes an
emotional expression with aggression and sentiment, an emotional
expression with impulse, an expression of desire regarding a
predetermined object. Furthermore, the statistical characteristic
includes a variety of statistics regarding a predetermined object
such as number of times and time, and techniques and means for
acquiring the variety of statistics.
[0072] The attribute (preference) is processed by being quantified
as a characteristic parameter. The quantification enables the
characteristics of the object to be censored and the related object
to be evaluated. For example, the attribute can extract the
expression of feelings and emotion of an individual person who has
generated an individual person generated data from an adjective
expression and an adverbial expression and the like contained in
text data based on the individual person generated data.
[0073] Specifically, when a predetermined object and a related
object are food, a variety of characteristics are included that are
objectively and subjectively discussed by an individual person with
regard to the predetermined object and the related object, such as
tasty, tasteless, sweet, spicy, hot, cold, want to eat again, never
want to eat again, etc., as the attribute regarding the
predetermined object and the related object. Furthermore, when a
predetermined object and a related object are a car, a variety of
characteristics are included that are objectively and subjectively
discussed by an individual person with regard to the predetermined
object and the related object, such as good at gas mileage, poor at
gas mileage, ecological, hybrid, large in size, small in size, want
to purchase definitely, not purchased yet, etc.
[0074] A step for extracting the characteristic text data that
satisfies the predetermined characteristic condition corresponds to
a "adaptive filter". The step generates a particle space. In this
case, the characteristic text data is extracted from the text data
based on the individual person generated data.
[0075] Although the fourth aspect of the present embodiment
described above illustrates the case where the characteristic text
data is extracted from the text data based on the individual person
generated data generated by an individual person, the
characteristic text data may be extracted from the decomposed text
data generated in the second aspect described above, or the
characteristic text data may be extracted from the related text
data generated in the third aspect described above.
[0076] <Case of Extracting Characteristic Text Data from Related
Text Data>
[0077] It is particularly desirable that the characteristic text
data is extracted from the related text data extracted in the third
aspect. Extracting the characteristic text data from the related
text data generates a partial space. In this case, the attribute is
not only a predetermined object, but also a variety of
characteristics such as properties and features of both the
predetermined object and the related object. The variety of
characteristics may be not only an objective characteristic, but
also the characteristic that is subjectively expressed based on
feeling and emotion. This makes it possible to extract not only the
characteristic text data indicating the attribute of the
predetermined object, but also the characteristic text data
indicating the attributes of both the predetermined object and the
related object.
[0078] Although an example of the field of censorship shown in FIG.
3A includes only five attributes (preferences), namely j=1 to 5,
the preference can be switched by making the characteristic
condition (adaptive filter) different as described above. The field
of censorship shown in FIG. 3A represent the example in the figure
in which five preferences are defined by using five characteristic
conditions (adaptive filters).
[0079] In the generated domain, one partial space can be specified
by defining the relation condition (basic filter) and the
characteristic condition (adaptive filter). Therefore, the
characteristic text data that satisfies the relation condition
(basic filter) and the characteristic condition (adaptive filter)
belong to the partial space.
[0080] For example, in the example of FIG. 3A, a domain (u.sub.2)
can be extracted by using a predetermined relation condition (basic
filter) (the relation condition corresponding to i=2). Then, a
partial space (e.sub.23) (i, j)=(2, 3) in the domain (u.sub.2) can
be extracted by using a predetermined characteristic condition
(adaptive filter) (the characteristic condition corresponding to
j=3) as a preference to the extracted domain (u.sub.2). That is, in
the example of FIG. 3A, one partial space can be extracted out of
twenty partial spaces (e.sub.11 to e.sub.45) by the predetermined
relation condition (basic filter) and the characteristic condition
(adaptive filter). Extracting the partial space enables the
characteristic text data belonging to the extracted partial space
to be extracted. For example, the characteristic text data
belonging to the partial space (i, j)=(2, 3) can be extracted.
[0081] As shown in FIG. 3A, each of four domains (u.sub.i) (i=1 to
4) is composed of five partial spaces. The domain (u.sub.1) is
composed of five partial spaces (e.sub.11 to e.sub.15), the domain
(u.sub.2) is composed of five partial spaces (e.sub.21 to
e.sub.25), the domain (u.sub.3) is composed of five partial spaces
(e.sub.31 to e.sub.35), and the domain (u.sub.4) is composed of
five partial spaces (e.sub.41 to e.sub.45).
[0082] The field of censorship can be configured by the partial
space generated based on a plurality of relation conditions (basic
filter) and a plurality of characteristic conditions (adaptive
filter). In the field of censorship, a plurality of desired partial
spaces can be specified by using a plurality of predetermined
relation conditions (basic filter) and a plurality of predetermined
characteristic conditions (adaptive filter). This enables an
operator of the censorship system to specify the partial space that
is desired to be censored because it is necessary.
[0083] Furthermore, the characteristic text data that satisfies the
predetermined characteristic condition can be extracted from both
the decomposed text data indicating the predetermined object and
the decomposed text data indicating the related object. That is,
the decomposed text data containing the object that satisfies the
predetermined characteristic condition either the predetermined
object or the related object is extracted as the characteristic
text data.
[0084] Furthermore, a distribution property composed of the
decomposed text data and the characteristic text data can be
extracted in the field of censorship. The distribution property
reflects the aspect of transmission of information after being
subject to repression and deformation in the field of censorship.
An operator of the censorship system can select one or a plurality
of partial spaces required to be censored, based on the
distribution property.
[0085] Yet further, the characteristic text data is stored in
connection with the predetermined characteristic condition. This
makes it possible to store not only the characteristic text data,
but also the predetermined characteristic condition by which the
characteristic text data is extracted. The condition of the
following processing thus can be appropriately defined.
[0086] <<Fifth Aspect>>
[0087] Furthermore, according to a fifth aspect of the present
embodiment, it is included the step of extracting particular text
data that satisfies a particular condition indicating a
predetermined particularity regarding an object indicated by text
data out of the text data based on individual person generated data
generated by an individual person.
[0088] A fifth aspect of the present embodiment will be described
with reference to FIG. 2D. First, a particular text data that
satisfies a particular condition indicating a predetermined
particularity is extracted from text data. The particular condition
indicating the predetermined particularity means the particularity
regarding a predetermined object, for example. The particularity
can be determined by whether a variety of amounts, degree and rate
of change regarding the predetermined object are larger or smaller
than a predetermined threshold value. The variety of amounts,
degree and rate of change are parameters which can be calculated by
predetermined computational processing and can characterize events
occurred regarding the predetermined object.
[0089] A step of extracting the particular text data that satisfies
the predetermined particular condition corresponds to a
"configuration filter." The step generates a candidate space. In
this case, the particular text data can be extracted from text data
based on an individual person generated data.
[0090] The particular text data that satisfies the particular
condition indicating the predetermined particularity regarding an
object indicated by the text data is extracted, so that the range
of the object to be monitored can be defined, and thus it is
possible to reduce the possibility that the result of monitoring
contains noise.
[0091] <<Sixth Aspect>>
[0092] Furthermore, according to a sixth aspect of the present
embodiment, it is included the steps of:
[0093] decomposing text data based on individual person generated
data generated by an individual person into decomposed text data
that can identify the meaning, and extracting related text data
indicating a related object that satisfies a certain relation
condition regarding an object indicated by the decomposed text data
out of the decomposed text data;
[0094] extracting characteristic text data that satisfies a
predetermined characteristic condition regarding an attribute of an
object indicated by text data out of the related text data; and
[0095] extracting particular text data that satisfies a particular
condition indicating a predetermined particularity regarding an
object indicated by the characteristic text data.
[0096] A sixth aspect of the present embodiment will be described
with reference to FIG. 2E. As shown in FIG. 2E, the configuration
can be made so that the particular text data is extracted from the
characteristic text data. Here, the characteristic text data
decomposes the text data based on the individual generated data
into the decomposed text data by a preference availability
operation for the censorship according to the second aspect. Then,
the related text data is extracted from the decomposed text data by
a preference availability operation for the censorship according to
the third aspect. Then, the characteristic text data is extracted
from the related text data based on the preference availability
operation for the censorship according to the fourth aspect. In the
preference availability operation for the censorship according to
the sixth aspect, the particular text data is extracted from the
characteristic text data extracted in this way.
[0097] In this manner, extracting the particular text data from the
characteristic text data can generate a candidate space inside of
the partial space. For example, in the example of the field of
censorship shown in FIG. 3(a), candidate spaces that satisfy the
particular condition indicating a predetermined particularity are
generated to twenty partial spaces. Satisfaction of the particular
condition results in the extraction of the candidate space. The
number of partial spaces constituting the candidate space may be
one or more.
[0098] The particular condition indicating the predetermined
particularity means the particularity regarding not only a
predetermined object but also both a predetermined object and a
related object. For example, it can be determined by whether a
variety of number, amount, degree and rate of change regarding the
predetermined object and the related object are larger or smaller
than a predetermined threshold value. The variety of number,
amount, degree and rate of change are parameters which can be
calculated by predetermined computational processing and can
characterize events occurred regarding the predetermined object and
the related object.
[0099] In particular, when a plurality of partial spaces is
configured and the predetermined object and the related object in a
part of partial spaces have some kind of particularity with regard
to the predetermined object and the related object in the rest of
the partial spaces, the step of extracting the particular text data
that satisfies the predetermined particular condition can extract
the particular text data indicating the predetermined object and
the related object contained in a part of partial spaces which is
determined as having the particularity.
[0100] For example, the number of times of appearance of a word
(transmission of information) of "ramen" in a part of partial
spaces in a predetermined domain is more frequent than in the rest
of partial spaces, the particular text data is extracted from the
related text data and the characteristic text data containing the
term "ramen" as satisfying the predetermined particular condition.
Furthermore, when the rate of change of the number of times of
appearance of the term indicating a product name of new product is
higher than in the rest of partial spaces, the particular text data
is extracted as satisfying the predetermined particular condition.
In this way, comparison regarding the predetermined object and the
related object is done among a plurality of partial spaces, it is
possible to acquire the partial spaces in which the predetermined
object and the related object are unbalanced, and the distorted
partial spaces. It is thus possible to determine the particularity
regarding the predetermined object and the related object to
extract the particular text data.
[0101] Furthermore, a single predetermined community described
below can be made to correspond to a single domain so as to find
the partial space having the particularity among a plurality of
communities, when a plurality of partial spaces are configured,
thereby determining the particularity regarding the predetermined
object and the related object.
[0102] The particular text data that satisfies the particular
condition indicating the predetermined particularity regarding an
object indicated by the text data is extracted, so that it is
possible to define the range of the object to be monitored based on
the predetermined relation condition (basic filter) and the
predetermined particular condition (adaptive filter), and thus it
is possible to reduce the possibility that the result of monitoring
contains noise.
[0103] Furthermore, an information availability technique is also
equipped which determines the importance of the particularity by
not only the presence of the particular text data, but also the
frequency of appearance and distribution of the particular
data.
[0104] <<Seventh Aspect>>
[0105] Furthermore, according to a seventh aspect of the present
embodiment, it is included the steps of:
[0106] generating historical information regarding history of an
object indicated by text data based on individual person generated
data generated by an individual person, and extracting historical
text data that satisfies a predetermined historical condition
regarding the historical information out of the text data based on
the individual person generated data; and
[0107] generating the number of reference in connection with a user
ID that can identify the individual person who has generated the
individual person generated data, the number of reference
indicating how many times the text data based on the individual
person generated data is referred to, and extracting reference text
data that satisfies a predetermined reference condition regarding
the number of reference out of the text data based on the
individual person generated data.
[0108] Here, a count as the number of reference is the count based
on the reference of data corresponding to the user ID for
identifying an individual person or posting number, which
corresponds to "RT" in the case of Twitter and corresponds to "Re:"
in the case of e-mail. For example, when a comment on a new product
is extracted, the importance of the posting by a person who has
posted in the first place is not necessarily increases with regard
to the product name of the new product mentioned by a person who
has posted in the first place, i.e., the abstracted term. The
number of reference does not refer to the abstracted data that
simply appears frequently and many times, but is for extracting the
fact that the posting is receiving attention, i.e. the number of
reference increases with regard to, for example, the posting made
by a celebrity, such as "Mr./Ms. A has said that," "the somethingth
posting has been mentioned in this way", and the like.
[0109] A seventh aspect of the present embodiment will be described
with reference to FIG. 2F. First, a historical information is
generated which relates to the history of an object indicated by
text data based on an individual person generated data generated by
an individual person. The historical information is the information
indicating the history regarding the object indicated by the text
data. For example, it includes the number and frequency showing
that a term regarding the object is contained in the text data, and
the number, frequency, and rate of appearance of the text data
containing the term regarding the object. This makes it possible to
acquire the number of times, frequency and rate of appearance of
information on the object that is generated in the past by an
individual person who has generated individual person generated
data. Using the historical information can provide the
determination not only by using a certain time of day and a certain
period of time, but also by including the state of progress and
change. Furthermore, the determination can be done using varying in
density level, frequency and number of times of something regarding
the predetermined object, and the degree of change in temporal
transition.
[0110] Furthermore, the historical text data that satisfies a
predetermined historical condition regarding the historical
information is extracted from the text data.
[0111] The number of reference indicating the number of times that
the text data based on the individual person generated data is
referred is generated in connection with the user ID. The number of
reference is the number that the text data based on the individual
person generated data is referred by other individual person. More
specifically, it is the number that the text data based on the
individual person generated data generated by a single individual
person is referred by other individual person.
[0112] Furthermore, reference text data that satisfies a
predetermined reference condition regarding the number of reference
is extracted from the text data based on the individual person
generated data.
[0113] The search can be done by the historical information while
including the situation changing with time. Furthermore,
enormousness of influence of an individual person corresponding to
the user ID can be acquired by the number of reference.
[0114] Although the seventh aspect of the present embodiment
described above has showed the case of generating the historical
information and extracting the historical text data from the text
data based on the individual person generated data generated by an
individual person, the historical data may be extracted from the
decomposed text data generated in the second aspect, from the
related text data extracted in the third aspect, and from the
characteristic text data extracted in the sixth aspect.
[0115] <Case of Extracting Characteristic Text Data from
Historical Text Data>
[0116] It is particularly desirable that the historical text data
is extracted from the characteristic text data extracted in the
sixth aspect. Extracting the historical text data form the
characteristic text data generates a monitoring space from the
candidate space. More specifically, as shown in FIG. 3(a), the
domain is generated by the third aspect, the partial space is
generated by the fourth aspect, the candidate space is generated by
the fifth aspect, and the monitoring space is generated by this
seventh aspect.
[0117] This case includes the number and frequency of the term in
relation to not only a predetermined object but also both the
predetermined object and a related object included in the text
data, frequency and rate of appearance of the text data containing
the term in relation to both the object and the related object,
etc. These make it possible to acquire the number of times,
frequency and rate of appearance of information on the object and
the related object that are generated in the past by an individual
person who has generated individual person generated data. Using
the historical information can provide the determination not only
by using a certain time of day and a certain period of time, but
also by including the state of progress and change. Furthermore,
the determination can be done using varying in density level,
frequency and the number of times of something regarding the
predetermined object, and the degree of change in temporal
transition. This makes it possible to extract and generate the
partial space changing with time as the monitoring space.
[0118] <<Eighth Aspect>>
[0119] Furthermore, according to an eighth aspect of the present
embodiment, it is included the step of generating monitoring
information based on the historical text data.
[0120] The monitoring mainly means for example, monitoring bases on
the historical text data, an individual person who has generated an
individual person generated data that is a source of the historical
text data, monitoring an object indicated by the historical text
data based on the historical text data, and monitoring both the
individual person and the object. The monitoring information is
information indicating the individual person and object to be
monitored, and the contents and methods of monitoring thereto.
Furthermore, the individual person to be monitored can be defined
by using the user ID.
[0121] <<Ninth Aspect>>
[0122] Furthermore, according to a ninth aspect of the present
embodiment, it is included the step of generating a censorship
control command based on the monitoring information.
[0123] The censorship control command is generated as a specific
executable command in response to the individual person and object
to be monitored, and to the contents and method of monitoring
thereto. For example, the censorship control command includes one
executable by software processing that transmits a predetermined
message and a predetermined data to the user ID to be monitored.
Furthermore, the censorship control command includes one executable
by hardware processing such as termination of the electrical
connection of the network. Furthermore, the censorship control
command may execute new information provision appropriate to
preference property of the individual person. In this way, it is
included not only repression and deformation of the provision of
service, but also execution of the provision of new service and
related information.
[0124] From the fact explained above, an information processing
system can be provided as follows. The information processing
system is provided with:
[0125] a field-of-censorship generation device for decomposing text
data based on individual person generated data generated by an
individual person into decomposed data that can identify the
meaning, extracting data that satisfies both a predetermined
relation condition regarding an object indicated by the decomposed
text data and a predetermined characteristic condition regarding
the object, and generating a collection of first extracted data
extracted thereby as a field of censorship; and
[0126] a device for making particularity available for extracting
data that satisfies a particular condition indicating a
predetermined particularity regarding the object from the
collection of the first extracted data, and detecting the
predetermined particularity from second extracted data extracted
thereby to make it available.
[0127] Furthermore, it is desirable that the information processing
system has a monitoring device for determining an individual person
to be monitored and the contents of monitoring for controlling the
monitoring based on the second extracted data.
[0128] <<Network Environment Including Monitoring
System>>
[0129] FIG. 4 is a diagram showing an example of a network to which
the monitoring system (the censorship system) of the present
embodiment is connected.
[0130] <<Network 10>>
[0131] On a network 10, a variety of terminal devices and a
monitoring system 100 are communicatively connected with one
another. On the network 10, nodes composed of a variety of
telecommunication equipment, such as a router and a hub (not
shown), is mutually connected to form a communication network. On
the network 10, communication can be established among a variety of
terminal devices and the monitoring system 100 which are connected
to the network 10, irrespective of the type of line such as wired,
wireless, leased, switched, a local area network. A variety of
information traveling across the network 10 is divided into a
plurality of packets and the like to be transferred among the
nodes. This makes it possible to transmit information from an
originating terminal device to a destination terminal device.
[0132] <<Terminal Device>>
[0133] The variety of terminal devices communicatively connected to
the network 10 include a computer 12, a cellular phone 14, a
fixed-line phone (including an IP telephone) 16, a portable
terminal device (not shown), etc. The portable terminal device is
connected to the network 10 via a wireless communication network
(not shown). Furthermore, the fixed-line phone 16 is connected to
the network 10 via a fixed-line network (not shown). The terminal
device is mainly operated by an individual person, and can send out
a variety of data input and generated by an individual person to
the network 10.
[0134] <<Server 20>>
[0135] A server 20 stores a variety of data input or generated at
the variety of terminal devices. The server 20 includes a variety
of servers such as a web server, a mail server, a database server,
etc. The server 20 is just necessary to be one in which stores the
data transmitted from the terminal device so that the monitoring
system 100 can read out the stored data via the network 10,
irrespective of the type, function, number thereof.
[0136] Furthermore, the server 20 also stores creator
identification data for identifying a creator who creates data
which is input of generated by the terminal device. The data itself
which is input or generated at the terminal device may contain the
creator identification data. Also, date/time data is stored which
indicates date and time of inputting or generating the data at the
terminal device. Such the creator identification data and the
date/time data are just necessary to be ones which are stored so
that the monitoring system 100 can read out, likewise the data
input or generated at the terminal device.
[0137] <<Monitoring System 100 (Censorship
System)>>
[0138] The monitoring system 100 is connected to the network 10
always or for each predetermined timing. The monitoring system 100
mainly collects and acquires a variety of data stored in the server
20. In addition, a variety of data sent from not the server 20 but
a variety of terminal devices may be collected. Either way, it is
just necessary to acquire, via a network, a variety of data
input/generated by an individual person operating a variety of
terminal devices. The case of acquiring a variety of data from the
server 20 will be described below.
[0139] The data input/generated at the terminal device is mainly
text data input/generated by an individual person. In addition, the
text data is just necessary to be one which can be converted into
text format if it is in binary format.
[0140] Those text data are just necessary to be the data which is
transmitted by an individual person via the network 10, as well as
the data in which the monitoring system 100 can collect via the
network 10, such as the data generated as blog, short data such as
so-called Twitter, etc. Specifically, it is just necessary that the
data is in text format which can be transmitted to the public by an
individual person and collected by the monitoring system 100.
[0141] Furthermore, the data input or generated at the terminal
device also includes the text data, as well as voice data, image
data, etc. Even the voice data and the image data can be converted
into the text data by a variety of recognition processing such as
voice recognition and image recognition. The monitoring system 100
is intended to process not only the data that is originally text
data, but also the data that is converted into text data. The
conversion from the voice data and the image data into the text
data may be executed in the monitoring system 100, or may be
executed outside of the monitoring system 100.
[0142] <<Configuration of Monitoring System 100>>
[0143] The monitoring system 100 has a central processing unit
(CPU), a random access memory (RAM), a read only memory (ROM), an
input/output interface (I/O), and an external storage device. These
operate in accordance with a predetermined program so as to
configure a field-of-censorship generation device, a monitoring
information extraction device, a candidate space generation device,
etc.
[0144] <<Conversion Device>>
[0145] The monitoring system 100 has the input/output interface
(I/O). The monitoring system 100 is connected to the network 10 via
the input/output interface (I/O). The monitoring system 100
collects a variety of data via the network 10. A conversion device
does not process text data if the collected data is text data. In
contrast, the conversion device selects recognition processing in
accordance with data format and converts the data into text data if
the collected data is voice data or image data. In addition, as
described above, the conversion of data may be executed in the
monitoring system 100, or may be executed outside of the monitoring
system 100.
[0146] In this way, the text data addressed in the monitoring
system 100 of the present embodiment includes the data that is
originally text data without undergoing the processing by the
conversion device, and the data that is converted into text data by
the conversion device. Those data are hereinafter referred to as
text data for processing. The text data for processing includes a
variety of words of interest such as a person, an article, a name
of place, etc.
[0147] <<Association of Text Data for Processing>>
[0148] As described above, the server 20 stores both the creator
identification data and the date/time data so that the monitoring
system 100 can read out the data. The creator identification data
and the date/time data are associated with the text data for
processing. This makes it possible to execute a search using a
creator who has created the text data for processing and date and
time of creation of the text data for processing.
[0149] <<Abstraction of Personal Data>>
[0150] The text data for processing is input or generated by a
diversity of individual persons. Accordingly, the text data for
processing may contain a variety of personal information. In terms
of protecting personal information, the monitoring system 100 of
the present embodiment executes the process of abstracting personal
information from the text data for processing. For example, a
personal name by which an individual person is identified, and
address, telephone number and e-mail address of the individual
person are determined, and then they are abstracted from the text
data for processing to process the text data for processing.
[0151] <<Generation of Related Terminology>>
[0152] The text data for processing is data indicating a variety of
objects expressed by a creator. For example, the object shows a
concept over a variety of fields such as famous person, food, cars,
music, travel, etc. In order to induce the data to indicate the
object, the processing is executed in which the text data for
processing is divided into unit data composed of minimum character
strings having a predetermined meaning. For example, the text data
for processing can be decomposed into unit data of morpheme by
being subjected to a morphological analysis. In addition, the
processing of dividing into the data indicating the object is not
limited to the morphological analysis, but may be the processing of
separating from the text data for processing to data of a desired
character string.
[0153] The text data for processing is associated with the creator
identification data and the date/time data. Therefore, the creator
identification data and the date/time data associated with the text
data for processing can be associated with the character string
data indicating the object as they are.
[0154] As described above, the object is the concept such as famous
persons, food, cars, music, travel, etc. Accordingly, there exists
a related object in relation to the object, such as a synonym, an
equivalent word, slang, etc. In order to prevent the omission of
search, at least data indicating a related object is added to data
indicating a single object. For example, using a predetermined
thesaurus makes it possible to derive the related object in
relation thereto, such as a synonym, an equivalent word, slang,
etc.
[0155] The preference availability system and the censorship system
will be described more specifically with reference to FIG. 5.
[0156] <First Stage>
[0157] As a first state, an abstraction program is executed, so
that various expressions to be input (text data) is processed to be
a related terminology (which is a plurality of decomposed text data
that can identify the meaning converted into a predefined related
text data) composed of a plurality of categories such as genre,
preference, dialect or feeling, etc. The process processing is
preprocessing for the process of analyzing whether or not there
exists in a group of related terminologies a previously prepared
particular related terminology that is desired to be monitored.
Executing the process processing makes it possible to avoid the
problem of leak of personal information even if the group of
related terminology itself is leaked to the outside.
[0158] The text data described above is input from outside via an
input interface. The person (hereinafter referred to as a censor)
to be an object of the censorship regarding a related terminology
as "a predetermined individual person" who has input the text data
can be identified by a user ID. The user ID and the related
terminology are linked to each other to be addressed as a pair.
[0159] The related terminology includes, for example, (1) a term
which expresses itself as being clearly an object to be censored;
(2) a term which can be recognized by people who is interested
therein as being an object to be censored; and (3) a slang which
can be recognized by experts as being an object to be censored.
Therefore, it is different from the censorship which extracts and
identifies only a user who transmits a predetermined word, such as
a hazardous word and a certain terminology, as in the conventional
manner.
[0160] For example, a person who is interested in a certain singer
may input compatibility with the singer, and a person who is
interested in cars may refer to a hybrid car and an electric car by
using expressions such as "an article suitable for energy-saving"
and "ecology". Therefore, when a computer executes the replacement
while linking "an article suitable for energy-saving" to the
related terminology, the word is replaced with "hybrid" or
"electricity" so that the field of censorship is generated thanks
to a first filtering processing (corresponding to, for example, the
basic filter). The generation of the field of censorship is
preprocessing of the following filtering for generating a partial
space and a monitoring space.
[0161] Moreover, as in the aforementioned (1) to (3), since the
related terminology to be replaced is composed of a different
plurality of filters (basic filters) in a different slang level,
the domains as many as the number of those basic filters are
resultingly generated. The basic filters at different slang levels
are updated, so that it is possible to render the filter suitable
for the case where the person to be an object to be censored
regarding the related terminology is a person who is familiar with
certain industry, and to render the filter unique to and suitable
for an operator who operates the censorship system (domain
terminology). The flexibility in designing of the censorship system
can be higher so as to provide the system which can be easy to
operate.
[0162] The domain is defined for each basic filter described
above.
[0163] Furthermore, in the case where the domain is generated with
raw text data as it is, the leakage of personal information to the
outside without approval of the person in question may cause a
legal problem. In such a case, a plurality of filters at different
slang levels is used to abstract the personal information and to
converted the data into the related terminology described above, so
that it is possible to avoid the problem of excluding the data from
the object to be censored.
[0164] In the domain, the censor and the related terminology are
linked to each other in that space, similar to a partial space, a
candidate space, and a monitoring space generated below.
[0165] <Second Stage>
[0166] Next, a second filtering processing is performed as a second
stage on the domain generated at the first stage, and thus a
partial space is generated corresponding to each of the second
filtering processing. Since the linkage of the censor with the
related terminology is maintained also in the second filtering
processing, the censor and the related terminology are linked with
each other even in the partial space generated by the second
filtering processing. While the censor and the related terminology
are addressed as a pair, the second filtering processing is
executed which is applicable to each of a plurality of kinds of
genres previously prepared. A plurality of kinds of filters for the
second filtering processing may enormous numbers of filters such as
hundreds and thousands.
[0167] More specifically, the filter for "the second filtering
processing which is applicable to each of a plurality of kinds of
genres previously prepared" may be a slang filter, a classification
filter, or a mentality filter. For example, the domain is filtered
regarding whether or not a certain single slang is used.
[0168] For example, in the case where the domain is a space which
is generated based on the contents of a web bulletin board for
being posted by students of a school, the second filtering
processing is performed by means of a single slang filter with
regard to a related terminology of "annoying" as a certain slang,
it is possible to extract a series of related text data groups to
which the user ID corresponding to the related terminology is
linked. In this case, the related terminology in relation to
bullying may be extracted.
[0169] Moreover, when the second filtering is performed by means of
the related terminology showing a certain mentality, the user ID in
relation to the mentality and a series of other related
terminologies (other related text data) in which the related
terminology concerned appears are extracted in the domain to
generated a partial space. Since there are various expressions as
slang depending on districts, local communities and industries, it
is desirable that the design is made so that the setting can be
done at the side of the operator who operates the censorship
system.
[0170] Furthermore, the setting may be done so that a single
related terminology is assigned to a plurality of decomposed text
data capable of identifying the meaning of the text data input from
outside. The configuration in this manner makes it possible to
monitor the pieces of decomposed text data having similar meaning
that is expressed in various ways by means of a single related
terminology. In this case, it is just necessary to be configured so
that a lookup table and the like for assigning a single terminology
to the decomposed text data is referred to.
[0171] Furthermore, in the case of monitoring newly input external
information in real time, it is possible to perform the monitoring
regarding whether or not the external information which is
expressed in many ways corresponds to the related terminology as
the monitoring information to be monitored, over a range broader
than the external information. In contrast, the related terminology
which is frequently used by the user ID to be monitored is regarded
as the object to be monitored as the new particular related
terminology, so that it is possible to easily monitor the change
moving with time.
[0172] The historical information is generated from the partial
space generated by the second filtering processing, and stored in a
historical information database. The historical information is
information which can designate the domain constituting the partial
space and designate the type of adaptive filter for use in the
second filtering processing, and characterize the domain to
determine what type of related terminology is contained.
[0173] Furthermore, an output interface can be provided in order to
output information in the historical database to the external
information availability device. The information availability
device includes, for example, ones which visually displays, in a
tabular form, date and time in which an external input is done, a
user ID for identifying an individual person who has input the
external information, and the related terminology group converted
from the external information, those being expressed by character
strings, or ones for visually displaying as a bar chart and a curve
graph on a display.
[0174] <Third Stage>
[0175] Furthermore, a third filtering processing as a third stage
is executed on the partial space generated at the second stage. The
third filtering processing is the filtering processing suitable for
determining whether or not it is in the particular situation with
regard to the related terminology contained in the partial space.
Specifically, the determination process is executed regarding
whether or not a predetermined particular condition is satisfied
for each related terminology at a certain different monitoring
level, and the related terminology satisfying the particular
condition is extracted as a candidate space. The extracted
candidate space contains the related text data for each user
ID.
[0176] "Whether or not a particular condition is satisfied" is that
the filtering is performed by a predefined determination in which,
if "drag", "murder", "bullying", "suicide", "nuclear bomb", and
"super yummy" which are set at the hazardous level in the slang
level appears even once, "pleasant", "nuclear", "disgusting",
"yummy" frequently appear (such as ten times) in a series of
external information.
[0177] <Fourth Stage>
[0178] In addition, a fourth filtering process program is executed
as a fourth stage in which it is determined whether or not the user
ID of an object of candidate described above from the historical
information based on the input date/time data described above in
the candidate space, and the setting in the monitoring space is
determined based on the candidate space containing the particular
factor described above of the user ID set as the object to be
monitored, as well as the related text data group in other partial
space with the different input date/time data of the user ID
similar to the above. Then, the related text data which has been
set in the monitoring space described above and the user ID to be
an object of monitoring are regarded as the monitoring information
described above, and are stored in a database retrievably for the
following monitoring. "Stored in a database retrievably for the
following monitoring" is that, in the case where a monitoring
information database which stores the monitoring information is
connected to the monitoring device and an external information is
the external information from the user ID of the object to be
monitored when input from the outside, a censorship command in
relation thereto is output to the outside, whereas, if not the user
ID of the object to be monitored, the censorship command in
relation thereto is output to the outside when there exists a
partial space containing the related terminology as being a
particular factor used by the object to be monitored.
[0179] <<Details of Censorship System According to the
Present Embodiment>>
[0180] <<Censorship>>
[0181] The censorship system according to the present embodiment
generates a concept of censorship in which a field formed by a user
of the main system is regarded as a field of censorship. Therefore,
the censorship in the censorship system according to the present
embodiment is characterized by function and service offered by the
censorship system, in contrast to a simple censorship.
[0182] The censorship system according to the present embodiment
may not only find and monitor an individual person who transmits
antisocialistic information and information counter to common
sense, but also find an individual person who is suffered for
psychological and/or mental instability and an individual person
who feel pain through the transmission of information so as to take
an appropriate action for protecting them. In this way, the
censorship system according to the present embodiment is the system
capable of addressing individual persons including their
psychological status and mental status.
[0183] <<Transmission of Information>>
[0184] In the present embodiment, transmission of information
refers to writing various information in mainly e-mail, SMS, blog,
Twitter, an input box on the web screen, a bulletin board, etc. The
contents of the transmitted information are the object to be
censored in the censorship system according to the present
embodiment. The censorship system of the present embodiment
acquires information written in e-mail, SMS, blog, Twitter, an
input box on the web screen, a bulletin board, etc., to analyze the
contents of the transmitted information. The information written in
e-mail, SMS, blog, Twitter, an input box on the web screen, a
bulletin board, etc., is mainly in text data format.
[0185] In addition, the censorship system of the present embodiment
addresses the data as the transmitted information and regards it as
the object to be censored even though it is in the voice or image
format, as long as the data is one that can be converted into text
data. For example, the data may be in a variety of formats such as
voice data and image data as long as it can be converted into text
data by executing the recognition processing. The censorship system
of the present embodiment analyses the contents using the converted
text data so as to be an object to be censored as the transmitted
information.
[0186] The transmitted information corresponds to "an individual
person generated data generated by an individual person" and "text
data based on the individual person generated data generated by an
individual person".
[0187] <<Personal Information>>
[0188] Personal information to be an object in the present
embodiment is information which can identify an individual person
by the information itself, such as name and address. In contrast,
in the case where the individual person cannot be identified only
by the information in question and the individual person can be
identified by referring to other information, the information is
not addressed as personal information. The censorship system of the
present embodiment abstracts and addresses the personal information
contained in the contents of information transmitted by an
individual person.
[0189] <<Related Terminology>>
[0190] The censorship system according to the present embodiment is
configured on the basis of keywords called related terminology, and
function and service provided by the censorship system are achieved
based on related information held in the related terminology.
Therefore, the related terminology is different from so-called
keywords for use in a usual search processing and the like. The
related terminology is different from simply keywords, and can link
a variety of information such as domain and preference with each
other in order to configure information such as historical
information and monitoring information described below.
[0191] The related terminology includes data for expressing a
predetermined object contained in the contents of the transmitted
information. The object contained in the transmitted information
is, for example, a specific and substantive article and an abstract
concept which an individual person wishes to express by
transmitting information.
[0192] The related terminology corresponds to "related text
data".
[0193] <<Unique ID (User ID)>>
[0194] A unique ID is information for identifying an individual
person who has transmitted information. The censorship system
manages the unique ID in connection to the contents of transmitted
information as the related terminology. The unique ID is not
personal information itself. The unique ID includes, for example,
telephone number, license number, IP address, handle name in a
bulletin board, etc. An individual person can be identified by
means of the unique ID by referring to other information.
Therefore, the personal information is never leaked form the
censorship system to the outside, and an operator of the censorship
system can identify an individual person using the unique ID.
[0195] <<Date/Time Information>>
[0196] Date/time information is information indicating the time of
transmission of information by an individual person, such as
year/month/day and hour/minute/second, etc. The censorship system
manages the date/time information in connection to the contents of
transmitted information as the related terminology, similar to the
unique ID. In addition, all of the information of year/month/day
and hour/minute/second is not necessarily used, and it is just
necessary to appropriately select and use the information desired
by an operator of the censorship system. For example, the date/time
information can be acquired form date/time of transmission of
e-mail, date/time at the time when the information has posted to
the bulletin board.
[0197] <<Domain>>
[0198] The censorship system according to the present embodiment
extracts the related terminology indicating a predetermined object
which is desired by an operator of the censorship system from the
contents of information transmitted by an individual person, and
regards the related terminology as an object to be censored. In
order to extract the related terminology indicating a predetermined
object from the contents of information transmitted by an
individual person, the censorship system initially uses the basic
filter.
[0199] Furthermore, the censorship system of the present embodiment
regards both the related terminology indicating a predetermined
object contained in the contents of information transmitted by an
individual person and the related terminology indicating a related
object in relation to the predetermined object, as the object to be
censored. As described above, the predetermined object is, for
example, a specific and substantive article and an abstract concept
which an individual person wishes to express by transmitting
information. Moreover, the related object is an object which is
expanded from the predetermined object by using a synonym, a same
meaning word, an equivalent meaning word, an association word, a
related word, as well as a slang which indicate the predetermined
object. Both the related terminology indicating the predetermined
object and the related terminology indicating the related object
expanded from the predetermined object are used to be regarded as
the objects of censorship.
[0200] The basic filter for use in the censorship system according
to the present embodiment is the filter for extracting both the
related terminology indicating a predetermined object desired by an
operator of the censorship system and the related terminology
indicating the related object in relation to the predetermined
object. Using the basic filter makes it possible to extract both
the related terminology indicating the predetermined object and the
related terminology indicating the related object so as to be the
objects to be censored. This makes it possible to regard a synonym,
slang and the like as the object to be censored, and thus the
censorship which is desired by an operator of the censorship system
can be achieved adequately.
[0201] In order to achieve the expansion from the predetermined
object to the related object, the basic filter may be configured
using a so-called thesaurus that is commonly available.
Furthermore, the basic filter may be configured using a thesaurus
which is accumulated and made by an operator of the censorship
system on his/her own accord. The censorship system is configured
so that an operator of the censorship system can appropriately
change the basic filter, and thus the related object can be
expanded to the range desired by an operator of the censorship
system, thereby achieving more adequate censorship.
[0202] At least one basic filter can be set. Both the related
terminology indicating the predetermined object and the related
terminology indicating the related object are extracted from the
contents of information transmitted by an individual person using a
single basic filter, so that a single domain can be formed. The
single domain is the region of collection including the related
terminology indicating the predetermined object extracted by the
basic filter and the related terminology indicating the related
object. When a plurality of basic filters is set, the domain is
formed corresponding to each thereof. This makes it possible to
extract the related terminology indicating a variety of
predetermined objects and the related terminology indicating the
related object, and thus the censorship can be executed more
reliably.
[0203] Filters for classifying the related terminology for each of
a plurality of types can be defined as a plurality of basic
filters. This makes it possible to classify and extract the
keywords (related terminologies) indicating a variety of objects
contained in the contents of information transmitted by an
individual person for each of the plurality of types, thereby
forming the domain in accordance with the extracted related
terminology. For example, the predetermined type includes a
predetermined genre, theme, category, etc.
[0204] FIG. 3(a) is a diagram showing an example of a partial space
and a field of censorship. In the field of censorship shown in FIG.
3(a), one cell means one partial space. The partial space will be
described below. The field of censorship shown in FIG. 3(a) is
composed of four domains (u.sub.1 to u.sub.4) formed of four basic
filters. As shown in FIG. 3(a), the domain is used for indicating a
plurality of basic filters (related conditions). Specifically, a
first basic filter corresponds to a first domain (i=1), a second
basic filter corresponds to a second domain (i=2), a third basic
filter corresponds to a third domain (i=3), and a fourth basic
filter corresponds to a fourth domain (i=4). In this way, the
domain is for classifying and identifying the plurality of basic
filters.
[0205] The first basic filter generates a domain (u.sub.1). The
first domain is a region of collection that is formed by the
related terminology extracted in accordance with the setting
condition of the first basic filter from the related terminology
indicating the predetermined object contained in the contents of
information transmitted by an individual person and the related
terminology indicating the related object. Likewise, a second
domain (u.sub.2) is a region of collection formed by the related
terminology indicating the predetermined object and the related
terminology indicating the related object that are extracted in
accordance with the setting condition of the second basic filter, a
third domain (u.sub.3) is a region of collection formed by the
related terminology indicating the predetermined object and the
related terminology indicating the related object that are
extracted in accordance with the setting condition of the third
basic filter, a fourth domain (u.sub.4) is a region of collection
formed by the related terminology indicating the predetermined
object and the related terminology indicating the related object
that are extracted in accordance with the setting condition of the
fourth basic filter. The domains are formed in this manner, so that
each of the domains contains at least one related terminology
indicating the predetermined object or related object.
[0206] <<Preference>>
[0207] The censorship system of the present embodiment censors the
contents of information transmitted by an individual person
including feeling thereof. In general, an individual person may
transmits information having good feeling about a predetermined
object or having bad feeling thereabout when transmitting
information on the predetermined object. For example, information
on a certain product may be transmitted with feeling of
dissatisfaction about the product, e.g., he/she never desires to
purchase or use it, or with feeling of satisfaction, e.g., he/she
would love to purchase it. Therefore, even if the individual person
transmits information on the same object, a simple keyword search
may provide search results including both one serving as a useful
reference and one serving as an unuseful reference. In terms of
such the status, it is facilitated that feeling about the
predetermined object can be acquired form the contents of
transmitted information so that the feeling itself also can be the
object to be censored.
[0208] The censorship system of the present embodiment addresses
the feeling about the predetermined object as preference regarding
the predetermined object. The preference is acquired by extracting
a word indicating a predetermined object, adjective, adverb, verb,
etc., from the contents of information transmitted by an individual
person, more specifically from text data such as e-mail, SMS, blog,
Twitter, an input box on the web screen, a bulletin board, etc.,
and classifying those adjective, adverb and verb to analyze the
preference regarding a predetermined object. A level of feeling
about the predetermined object is also analyzed at that time. For
example, the level of feeling is included to be addressed as the
preference, such as having very good feeling, having good feeling
to some extent, having not so good feeling, having very bad
feeling, etc. Furthermore, the number of times of expressing the
feeling is also addressed as the preference. Specifically, the
facts of offering compliments on the product many times or speaking
ill of the product many times, and transmitting information only
once are addressed as the preference.
[0209] The preference is not only limited to the expression based
on feeling, but also includes the expression based on mentality.
Specifically, the preference is a characteristic that is
objectively expressed based on feeling and mentality about a
predetermined object contained in information transmitted by an
individual person. In other words, the preference is what an
individual person feels, considers, and thinks regarding a
predetermined object. The preference is just necessary to be an
objective expression which can be extracted from text data such as
e-mail, SMS, blog, Twitter, an input box on the web screen, a
bulletin board, etc. The preference is designed to be
characteristically parameterized based on the text data, and then
addressed computably as numerical values.
[0210] The censorship system of the present embodiment uses an
adaptive filter for extracting preference regarding a predetermined
object from the contents of information transmitted by an
individual person. At least one adaptive filter can be set. The
preference regarding the predetermined object can be extracted from
the contents of information transmitted by an individual person
using a single adaptive filter. A single preference indicates the
preference that is extracted by a single adaptive filter, and also
the preference regarding the predetermined object. When a plurality
of adaptive filters is set, the preference is extracted for each
thereof. This makes it possible to extract a variety of preferences
regarding a predetermined object including feeling and mental
status toward the predetermined object.
[0211] As described above, FIG. 3(a) is a diagram showing an
example of a partial space and a field of censorship. In the field
of censorship shown in FIG. 3(a), one cell means one partial space.
The partial space will be described below. The field of censorship
is a space composed of collection of text data which is acquired
form the contents of information transmitted by an individual
person so as to be an object to be censored, for example. More
specifically, the field of censorship is composed of at least one
text data to be an object to be censored, and is composed the
collection of a plurality of pieces of text data if any. The field
of censorship is, for example, a space (plane) having an axis of
preference as the lateral axis and an axis of domain as the
vertical axis, as shown in FIG. 3(a). Furthermore, the field of
censorship can be the space having an axis of time in addition to
the axis of preference and the axis of domain, as shown in FIG.
3(b).
[0212] As described above, the field of censorship is a space
composed of collection of text data to be an object to be censored.
The collection is not necessarily a concept of set for use in
mathematics, but is just necessary to be formed by collecting text
data. Moreover, identical text data may constitute a plurality of
collections. For example, the field of censorship may be configured
by constituting first and second collections by identical text
data. Furthermore, for example, a single collection can constitute
a single partial space.
[0213] The field of censorship shown in FIG. 3(a) has five
preferences (j=1 to 5) corresponding to each of five adaptive
filters. As shown in FIG. 3(a), the preferences for indicating a
plurality of adaptive filters (characteristic conditions) are used.
More specifically, a first adaptive filter corresponds to a first
preference (j=1), a second adaptive filter corresponds to a second
preference (j=2), a third adaptive filter corresponds to a third
preference (j=3), a fourth adaptive filter corresponds to a fourth
preference (j=4), and a fifth adaptive filter corresponds to a
fifth preference (j=5). In this way, the adaptive filter is for
classifying and identifying a plurality of preferences.
[0214] The partial space contained in the first preference is the
region of collection formed by the preference extracted in
accordance with the setting condition of the first adaptive filter
from various preferences regarding the predetermined object
contained in the contents of information transmitted by an
individual person and regarding the related object. Likewise, the
partial space contained in the second preference (j=2) is a region
of collection formed by the preferences regarding the predetermined
object and the related object in accordance with the setting
condition of the second adaptive filter, the partial space
contained in the third preference (j=3) is a region of collection
formed by the preferences regarding the predetermined object and
the related object in accordance with the setting condition of the
third adaptive filter, the partial space contained in the fourth
preference (j=4) is a region of collection formed by the
preferences regarding the predetermined object and the related
object in accordance with the setting condition of the fourth
adaptive filter, and the partial space contained in the fifth
preference (j=5) is a region of collection formed by the
preferences regarding the predetermined object and the related
object in accordance with the setting condition of the fifth
adaptive filter,
[0215] As described above, in the field of censorship shown in FIG.
3(a), one cell means one partial space. As described below, the
domain is generated by the basic filter, and the partial space is
generated by extracting from the domain by means of the adaptive
filter.
[0216] <<Basic Filter, Adaptive Filter, Partial
Space>>
[0217] FIG. 6 is a diagram showing an overview of the basic filter,
the adaptive filter, and the partial space.
[0218] <Basic Filter>
[0219] The basic filter is a filter for extracting the related
terminology out of information transmitted by an individual person
which is to be an object to be censored by the censorship system
according to the present embodiment. For example, the information
transmitted by an individual person is a lot of accumulated
personal data, as shown in FIG. 6. The personal data may be the
data accumulated in a predetermined server, or the data collected
and accumulated by the censorship system.
[0220] The basic filter can extract not only the related
terminology indicating a predetermined object contained in the
contents of information transmitted by an individual person, but
also the related terminology indicating the related object in
relation to the predetermined object. Using the basic filter makes
it possible to include, as the object to be censored, the word
which can be evoked by the object indicated by the related
terminology and is in relation to the related terminology, a slang
of the related terminology, a synonym of the related terminology,
etc., in addition to a simple related terminology.
[0221] As shown in FIG. 6, the levels of slang of the related
terminology constituting the basic filter can be set as follows:
level A: the terminology which can be publicly understood as being
clearly an object to be censored; level B: the terminology which
can be understood by people who is interested in as being an object
to be censored; and level C: a terminology which can be understood
by a specialist of the related terminology as being an object to be
censored. Furthermore, the slang can be made available by selecting
the slang level. For example, even though the slang at level C is
obscured by a bunch of existing slangs at level A, they can be made
available to compare with one another.
[0222] The predetermined related terminology is extracted by the
basic filter from information transmitted by an individual person,
thereby generating the domain. Specifically, the predetermined
related terminology is extracted by i-th basic filter from
information transmitted by an individual person, thereby generating
i-th domain u, by the extracted related terminology, as shown in
FIG. 6. In the domain u.sub.i the extracted related terminology is
linked with a person regarded as an object to be censored
(hereinafter referred to as the censored). The censored is a person
who is identified by the unique ID described above.
[0223] The domain u.sub.i is generated corresponding to the basic
filter. As shown in FIG. 3(a), a plurality of domains u, can be
generated from the information transmitted by an individual person
by changing the basic filter to address.
[0224] The domain u.sub.i is generated by the basic filter in a
partial space generation device. In the partial space generation
device, an operator can set the basic filter, the related
terminology specific to the operator can be extracted from
information transmitted by an individual person, and the related
terminology can be completely extracted from information
transmitted by an individual person. The domain is a collection
configured by the related terminologies (keywords). Furthermore,
the domain is a space which links the extracted related terminology
with the unique ID, and includes a collection of pairs of the
related terminology to be an object to be censored and the censored
while adjusting the slang level.
[0225] The related terminology may be collected by a related
terminology collection device. Furthermore, a synonym such as slang
can be expanded by a synonym expansion support device. The related
terminology collection device and the synonym expansion support
device are managed and operated by an operator so that the operator
of the censorship system can execute the censorship as desired.
[0226] <Adaptive Filter>
[0227] The adaptive filter is a filter for extracting preference
about a predetermined object from the contents of information
transmitted by an individual person. As described above, the
preference is a characteristic that is objectively expressed based
on feeling and mentality about a predetermined object contained in
information transmitted by an individual person. That is, the
preference is what an individual person feels, considers, and
thinks regarding a predetermined object. The preference is designed
to be characteristically parameterized based on the text data, and
then addressed computably as numerical values.
[0228] As shown in FIG. 6, the adaptive filter may be composed of a
classification filter, a slang filter, and a mentality filter. The
classification filter is a filter for classifying and extracting
the preference about a predetermined object indicated by the
related terminology. The slang filter is a filter for making it
possible to extract the preference about a predetermined object
even if it is expressed by slang. The mentality filter is a filter
for making it possible to extract the expression based on mentality
about a predetermined object.
[0229] The adaptive filter is composed of at least one of the
classification filter, the slang filter and the mentality filter.
When there is more than one kind of classification filter, the
slang filter and the mentality filter, respectively, the
combination thereof may constitute one adaptive filter. For
example, the combination of the classification filter, the slang
filter and the mentality filter constitute j-th adaptive filter
C.sub.j.
[0230] <Partial Space>
[0231] As described above, a domain u, is generated from
information transmitted by an individual person in accordance with
the basic filter. The j-th adaptive filter Cj is used to the domain
ui to calculate u.sub.i .andgate. C.sub.j, so that the related
terminology satisfying the adaptive filter C.sub.j is extracted
from the related terminology contained in the domain u.sub.i,
thereby generating a partial space e.sub.ij by the extracted
related terminology. The processing executed in this way results in
the partial space e.sub.ij as being the collection composed of the
related terminology that is extracted by both the basic filter
(i-th domain) and the adaptive filter C.sub.j out of the related
terminology contained in information transmitted by an individual
person. Furthermore, the partial space is a space which links the
extracted related terminology with the unique ID, and includes a
collection of pairs of the related terminology to be an object to
be censored and the censored, similar to the domain.
[0232] The partial space generation device generates the partial
space e.sub.ij from the related terminology contained in the domain
u.sub.i using the adaptive filter C.sub.j. In the partial space
generation device, an operator can set the adaptive filter, the
preference specific to the operator can be extracted from
information transmitted by an individual person, and the preference
can be completely extracted from information transmitted by an
individual person.
[0233] The basic filter corresponds to "the predetermined related
condition". The adaptive filter corresponds to "the predetermined
characteristic condition". The related terminology contained in the
partial space corresponds to "the first extracted data" and "the
characteristic text data".
[0234] <<Configuration Filter, Candidate Space>>
[0235] FIG. 7 is a diagram showing an overview of a configuration
filter and a candidate space generation device.
[0236] The configuration filter is the filter for extracting the
related terminology indicating particularity out of the related
terminologies contained in the partial space e.sub.ij. For example,
the configuration filter is the filter for extracting the related
terminology that satisfies the particular condition such as the
fact that information on a predetermined object has been
transmitted remarkably many times, transmission of information has
been suddenly started since a certain point of time, or the
like.
[0237] The partial space containing the related terminology that
satisfies the particular condition is extracted out of the partial
space extracted by the adaptive filter, and the candidate space is
generated from the extracted partial space.
[0238] The particular condition can be represented by the condition
based on various related terminology properties defined with regard
to a pair x of the censored and the related terminology, as shown
in FIG. 7.
[0239] The related terminology property includes, for example, an
attribute i of i-th related terminology, a slang level Li of i-th
related terminology, a frequency Ni in the field of censorship
regarding i-th related terminology, a rate of appearance Ni/Nd in
the field of censorship regarding i-th related terminology (Nd: the
number of entire related terminologies), a frequency ni in the
partial space regarding i-th related terminology, a rate of
appearance ni/ns of related terminology i in the partial space (ns:
the number of entire related terminologies), a weight of the
partial space .alpha. (=ns/Nd), a particularity index of i-th
related terminology (=(ni/Ni)/.alpha.), etc.
[0240] Furthermore, it is possible to use Si, Si/Sd, si, si/ss,
.beta.=ss/Sd, and s=(si/Si)/.beta. as the particular conditions.
These are parameters indicating cover rate in the partial space: Sd
is the number of censored sentences in the field of censorship, and
ss is the number of censored sentences in the partial space.
[0241] Using such a variety of related terminology properties makes
it easy to find the related terminology which represents the
particularity. The partial space containing the related terminology
which represents the particularity is extracted to generate the
candidate space. For example, the particularity in the partial
space has the characteristic such as bias or skewness of the
existence of related terminology in the partial space.
[0242] As shown in FIG. 7, the adaptive filter corresponding to the
particular condition c.sub.ij of the related terminology is used to
compute .sigma..sub.ij={x|x
.ANG..sub.ij,.DELTA.(x).gtoreq.c.sub.ij}, so that the related
terminology satisfying the particular condition c.sub.ij is
extracted from the related terminology containing the partial space
e.sub.ij generated by the adaptive filter, thereby generating the
candidate space .sigma..sub.ij by the extracted terminology. The
processing executed in this way results in the candidate space
.sigma..sub.ij as being the collection composed of the related
terminology that is extracted by three kinds of filters, i.e., the
basic filter (i-th domain), the adaptive filter C.sub.j, and the
configuration filter, out of the related terminology contained in
information transmitted by an individual person. Furthermore, the
candidate space is a space which links the extracted related
terminology with the unique ID, and includes a collection of pairs
of the related terminology to be an object to be censored and the
censored, similar to the partial space. The censored is a person
who is identified by the unique ID described above.
[0243] The candidate space generation device generates the
candidate space .sigma..sub.ij from the related terminology
contained in the partial space e.sub.ij using the related
terminology satisfying the particular condition c.sub.ij using the
adaptive filter C.sub.j. In the candidate space generation device,
the particularity property of the related terminology can be
defined for each domain and preference designated by the operator
side, so that it is possible to extract the censored and the
related terminology which lead directly to the service at the
operator side. The related terminology extracted using the
configuration filter is referred to as a particular related
terminology. Furthermore, the censored who is linked with the
related terminology extracted using the configuration filter is
referred to as the candidate (a person who should be
monitored).
[0244] The adaptive filter corresponds to "the particular condition
indicating a predetermined particularity". The related terminology
contained in the candidate space corresponds to "the particular
related text data".
[0245] <<Balancing Filter, Monitoring Space>>
[0246] FIG. 8 is a diagram showing an overview of the balancing
filter and the monitoring space generation device.
[0247] The balancing filter is the filter for extracting the
related terminology satisfying a predetermined historical condition
and generating a monitoring space. The historical condition is the
condition in relation to the related terminology. For example, the
historical condition is the condition which can be defined from the
history regarding the related terminology which is always in
information transmitted by a certain individual person, the related
terminology which is in information transmitted by a certain
individual person for the first time, or the related terminology
which is in information currently transmitted and talked by many
individual persons. Executing a variety of statistical processing
with regard to the related terminology makes it possible to
determine whether or not the historical condition is satisfied.
[0248] For example, the balancing filter corresponding to a
historical condition hist.sub.ij regarding the related terminology
is used to compute f.sub.ij={(m,w,h)|x=(m,w) .di-elect
cons..sigma..sub.ij,h.di-elect cons. hist.sub.ij }, so that the
related terminology satisfying the historical condition hist.sub.ij
is extracted from the related terminology contained in the
candidate space .sigma..sub.ij generated by the configuration
filter, thereby generating the monitoring space f.sub.ij by the
extracted related terminology; where h=h(frequency(x),
reference(m)). The processing executed in this way results in the
monitoring space f.sub.ij as being the collection composed of the
related terminologies that are extracted by four kinds of filters,
i.e., the basic filter (i-th domain), the adaptive filter C.sub.j,
the configuration filter, and the balancing filter out of the
related terminology contained in information transmitted by an
individual person. Furthermore, the monitoring space is a space
which links the extracted related terminology with the unique ID,
and includes a collection of pairs of the related terminology to be
an object to be censored and the censored, similar to the partial
space and the candidate space. The censored is a person who is
identified by the unique ID described above.
[0249] The monitoring space generation device generates the
monitoring space f.sub.ij from the related terminology contained in
the candidate space .sigma..sub.ij using the related terminology
satisfying the historical condition hist.sub.ij using the balancing
filter. In the monitoring space generation device, the historical
condition can be defined for each domain and preference designated
by the operator side, so that it is possible to extract the
censored and the particular related terminology which lead directly
to the service at the operator side.
[0250] As shown in FIGS. 8 and 9, the historical availability
device of x .di-elect cons..sigma..sub.ij can be configured with
regard to the candidate space .sigma..sub.ij, and the historical
availability device of y .di-elect cons.f.sub.ij can be configured
with regard to the monitoring space f.sub.ij. The historical
availability devices of these types are configured, so that it is
possible to configure a day-to-day variation information
availability device for indicating the day-to-day variation and a
within-day variation information availability device for indicating
the variation within a day. A variety of data thus can be
displayed.
[0251] For example, acquiring such the historical property makes it
possible to detect the partial space in which the particularity
changes in with time of day, as shown in FIG. 3(b). Therefore, it
is possible to detect the partial space in which the information is
not only one that is currently transmitted or transmitted at a
certain time of day in the past, but also one that the contents
thereof gradually changes and suddenly changes. An individual
person who transmitted information in the same way can be an object
to be censored. Furthermore, the estimation in future can be done
by the change in time of day, and thus it can be determined whether
or not it should be monitored from this time forward.
[0252] The balancing filter corresponds to "the predetermined
historical condition". The related terminology contained in the
candidate space corresponds to "the historical text data".
[0253] <<<Censorship System Available
Online>>>
[0254] FIG. 10 is a block diagram showing an overview of a
preference availability system (censorship system) available
online.
[0255] A related terminology extraction device shown in FIG. 10 is
composed of the partial space generation device described above
(refer to FIG. 11). The partial space generation device executes
the processing in the same way as described above. More
specifically, the domain u, is generated from information
transmitted by an individual person by the basic filter, and the
partial space e.sub.ij is generated from the domain u.sub.i by the
adaptive filter.
[0256] Furthermore, the related terminology extraction device has a
monitoring device (refer to FIG. 12). The monitoring device refers
to monitoring information based on the related terminology
contained in the partial space e.sub.ij and the unique ID (the
censored) so as to acquire the censored to be monitored (the
monitored), the related terminology in which the particularity has
been found (a particular related terminology), and a historical
property regarding the particular related terminology, from the
monitoring information. The monitoring device outputs the acquired
monitored, particular related terminology, and historical property
to a censorship control device. In addition, in the case where
information such as advertisement of a new product is provided to a
plurality of individual persons, the censored may not be the
monitored. In this case, the monitoring device outputs the censored
and the related terminology to the censorship control device.
[0257] The censorship control device acquires a censorship control
command based on the monitoring information such as the particular
related terminology and the historical property, and then outputs
it to an output conversion device (refer to FIG. 13). The
censorship control command includes, for example, ignore (normality
guaranteed), alert (security), statistic (customer service),
recommend (advertisement), education (risk management),
encouragement (caregiving), entertainment information (rich
spirit), etc. The censorship control command is stored in a table
so as to be able to be selected in accordance with the particular
related terminology and the historical property.
[0258] The censorship control device transmits output information
to the output conversion device in accordance with the contents of
those censorship control commands. When the output information is
output from the output conversion device, an output log is
generated for storing the contents thereof, day and time, the
output unique ID so as to be stored in the output storage device.
Moreover, the output conversion device refers to the output log
stored in the output storage device to determine whether or not the
output information is to be output. For example, when the output
information has been already output to an individual person
indicated by the existing unique ID, the output of the output
information is stopped.
[0259] FIG. 11 shows the basic filter and the adaptive filter in
the censorship system available online, in which the same
processing as described above is executed. Specifically, the domain
u.sub.i is generated form information transmitted by an individual
person by the basic filter, and the partial space e.sub.ij is
generated from the domain u.sub.i by the adaptive filter.
[0260] <<Censorship Control Command>>
[0261] The censorship control command is the command for
transmitting alert information to an individual person who is an
object to be censored, and transmitting encouraging information, as
a result of censorship. Furthermore, the censorship control command
is the command for controlling a device and a system which are used
by an individual person. Transmitting the censorship control
command in this manner makes it possible to terminate the
communication line of the device and system which are used by an
individual person who is transmitting antisocialistic information
and information counter to common sense. The censorship control
command of this type can define the contents desired by an operator
of the censorship system in accordance with the result of
censorship.
EXAMPLE 1
[0262] FIG. 14 shows an example in which the present invention is
applied to a main system which can execute an electronic commerce
(e-commerce) for making contract and payment utilizing a network
such as the Internet.
[0263] E-commerce is roughly classified in three types in general,
that is, a business-to-business transaction is called "B to B", a
business-to-consumer transaction is called "B to C", and a
consumer-to-consumer transaction is called "C to C".
[0264] A typical B-to-B EC site to which the present invention is
applied in this example is connected to a terminal of a plurality
of individual persons over a network such as the Internet with a
center focus on the main system, and is connected to a personal
information database of the individual persons accessed through
each of the terminals. Then, various input information is acquired
from a plurality of terminal groups. In the inside of the main
system, a plurality of genres of communities implicitly exists,
such as a cartoon film community for those who like cartoon films
and are interested in cartoon films, a gourmet community for those
who mainly transmit information on foods, or the like. However, in
the communities, it has been typical that groups are not available
(groups cannot be extracted or there is no mechanism to extract
groups).
[0265] Furthermore, as one of those EC sites, the cooperation with
the main system which operates a gourmet search site ("Gourmet
Navi" in FIG. 14) is achieved in this example. The present
invention cooperates with the EC site, and thus the preference
availability system and the censorship system (hereinafter referred
to as an information processing system) can execute active
processing such as interactive information provision and
communication termination at the terminal side in accordance with
input information input by an individual person on the search
screen that is downloaded from the main system by accessing the
main system through the terminal.
[0266] For example, the case will be considered in which an input
information "a `meeting curry` will be held? But I want to eat
delicious pasta or ramen." is transmitted as the text input to the
main server through the terminal of an individual person. When the
input information is input through an input interface of the
information processing system, an input conversion device converts
it into a single data format (text information in the case of this
example) that is addressed in the information processing system.
The input information is not only a method of executing text input
by key input using a keyboard or a touch panel, but an input scheme
by a voice recognition described below can be employed for the
input information of the present invention.
[0267] Here, the information processing system of this embodiment
described above is composed of the preference availability system
and the censorship system, as well as a historical information
database (historical information DB), a monitoring information
database (monitoring information DB), a filter editing controller
for editing a variety of filters, and a command editing control
device for editing a variety of censorship control commands.
[0268] Furthermore, the censorship system described above is
provides with an output conversion device for outputting the
censorship control command to the aforementioned input conversion
device and to the outside in an appropriate output format, a
censorship control command database (censorship control command DB)
which stores a variety of commands edited by the command editing
control device, a censorship control device which refers to the
censorship control command database in accordance with the
monitoring information output from the preference availability
system so as to output the command to the main system via the
output conversion device, and an output log storage device for
storing output logs of a variety of censorship control commands
output from the output conversion device.
[0269] Furthermore, the preference availability system is provided
with the related terminal extraction device and the monitoring
information extraction system, as well as the filter editing device
for editing a variety of filters by the input from the filter
editing controller. As functions of each of the devices, the
functions are provided which are described in the embodiments
described above. Furthermore, the preference availability system in
question is also provided with a part of making the history
available with reference to the historical information data, and a
monitoring device which outputs monitoring information to the
censorship control device with reference to the monitoring
information database in accordance with information output from the
related terminology extraction device and monitoring information
extraction device.
[0270] In accordance with the information processing system
described above, when the input information such as "a "meeting
curry" will be held? But I want to eat delicious pasta or ramen" is
input, the processing data is generated from each of the input
information in the state inside thereof as follows (refer to FIG.
14).
[0271] Specifically, with regard to the input information of
"meeting" as the related terminology, a single domain is that it is
an NG word to which an alert should be issued, and the related
terminology of "meeting" is addressed in the historical definition
to be done by a new comer when this information is transmitted by
an ID of an individual person for the first time. Thus, the
processing data of alert is generated as a command for censoring
and controlling.
[0272] Furthermore, with regard to the input information of the
related terminology of pasta, the domain is noodles, the preference
is regarded as "like" depending on the fact that the individual
person has transmitted information many times and on the contents
of transmitted information, and the historical property is regarded
as being a regular customer with reference to the historical
information. Commands of "past" and "recommended" are thus provided
in accordance with those results.
[0273] Furthermore, with regard to the input information of related
terminology of ramen, the domain is noodles, the preference is
regarded as "like" depending on the fact that the individual person
has transmitted information of "ramen" many times and on the
contents of transmitted information, and the historical property is
regarded as being a regular customer because he/she has transmitted
information over and over again.
[0274] Then, the processing data as the status inside thereof
described above is generated as follows. When the input information
from the main system is acquired at the information processing
system, the processing is executed for changing/unifying the input
information in the processible data format such as text. Then, the
censorship space generation device and the partial space generation
device of the related terminology extraction device execute the
processing on the data using the aforementioned basic filter and
the adaptive filter while referring to the historical information
database, thereby initially generating the field of censorship
described above.
[0275] Then, the candidate space generation device and the
monitoring space generation device of the monitoring information
extraction device described above outputs the monitoring
information to the censorship system via the monitoring device by
executing the processing using the configuration filter and the
balancing filter as described above while referring to the
monitoring information database. Then the censorship control device
extracts a command in accordance with the output information from
the command database, and outputs the command to the main system in
order to provide the result to the terminal via the aforementioned
output conversion device.
[0276] "To provide the result to the terminal" includes providing
various concierge-like information, as well as an action in which,
in the case where the NG word domain is generated, the
communication line between the main system and the terminal of an
individual person is forcedly terminated if the individual person
transmits NG word information beyond a certain defined threshold
value. Namely, the censorship control command output to the main
system executes the provision of individual service tailored to the
preference of a customer, and the output control suitable for the
risk status of the input contents. In the case of the
aforementioned gourmet site, the search on the gourmet is
controlled to provide the result to an individual person (a
customer) in accordance with the censorship control command.
[0277] The example 1 is as described above. The information
processing system of the present invention is characterized to be
provided with a field-of-censorship generation function for
executing a plurality kinds of filtering processes to a plurality
of kinds of input information from terminals of a plurality of
individual persons acquired via the main system; and a monitoring
function for executing an availability function for making input
information newly input from the main system available, and
outputting the censorship control command to execute one of the
censorship control commands previously prepared as a result of the
aforementioned execution to the main system at the terminal from
which the input information is acquired.
EXAMPLE 2
[0278] While Example 1 has illustrated the example in which the
present invention is applied to the EC site, FIG. 15 shows Example
2 which is the example of cooperating the main system for providing
an artificial intelligence service which supports a customer with
the present invention. The basic configuration of the information
processing system in Example 2 is similar to that illustrated in
Example 1, and what is different from Example 1 is that the main
system to be cooperated is different, and each of the filters is
different because the input information to be input is different
due to the difference of the cooperated main system, and
resultingly the censorship control command for outputting to the
main system is different.
[0279] More specifically, in this Example 2, since the main system
is for providing the artificial intelligence service which supports
a customer, "I'm going to ask question about Caiwa (product name).
Please tell me how to introduce it." Can be considered as the input
information input to the aforementioned main system, for example.
In this case, as shown in FIG. 15, the inside status as a result of
the execution of the data processing in order to output the
censorship control command is as follows: with regard to the
related terminology of "Caiwa", the domain is "product" depending
on the fact that "Caiwa" is a product name, it is regarded as "an
important customer" depending on the ID of the individual person,
the domain of "product", and the historical information, and the
preference is regarded as "question" depending on the transmitted
information of "question" in the input information. The censorship
control commands output as a result to the main system are stored
as "important customer", "product" and "question". Moreover, the
related terminology of "introduce" is addressed in such a way that
the domain is "business", the preference is "question" depending on
the transmitted information of "please tell me", and the historical
property is "new comer" with reference to the historical
information. Output commands is output to the main system as the
censorship control command as a result of "new comer", "business",
and "question".
EXAMPLE 3
[0280] While Example 1 has illustrated the example in which the
present invention is applied to the EC site and Example 2 has
illustrated the example in which the present invention is applied
to the main system responsible for the customer service in the an
artificial intelligence service, FIG. 16 shows Example 3 which is
the example in which the present invention is applied to a main
system responsible for a robot voice control service. The basic
configuration of the information processing system in this Example
is similar to those illustrated in Examples 1 and 2, and what is
different from Examples 1 and 2 is that the main system to be
cooperated is different, and each of the filters is different
because the input information to be input is different due to the
difference of the cooperated main system, and resultingly the
censorship control command for outputting to the main system is
different. In addition, what is different is that the input from
the terminal in Example 3 is executed by a voice input while the
input scheme therefrom in the aforementioned Examples 1 and 2 is
mainly from a keyboard, and that the amount of characteristic of
voice is replaced with text data to make use thereof.
[0281] Then, since it is a voice input, the aforementioned filters
are prepared so that the amount of characteristic such as intensity
of volume has an effect on the input voice. The domain in
accordance with feeling is to be generated depending on the
intensity of volume.
[0282] Specifically, the case will be considered in which the main
system displays a guide screen "please speak" for facilitating the
transmission of information to a monitor at the terminal side, and
then a voice input "Fool!" is done to a microphone connected to the
terminal in a loud voice with the volume beyond a predetermined
threshold value. Of course, the aforementioned guide screen may be
of a system for bidirectionally interacting through a robot,
instead of the web screen.
[0283] The voice input in this case is regarded as "loud voice"
because it has been made with the volume beyond the certain
threshold value, and thus the domain is "volume", the preference is
"anger", and the historical property is "problematic customer" with
reference to the past history. As a result, the censorship control
commands are "problematic customer", "loud voice", and "anger".
Furthermore, by means of the filter of length of sentence, the
related terminology is regarded as "short sentence" because the
voice input "fool" is short, the domain is "length of sentence",
and the historical property is "general customer" depending on the
past history. The censorship control commands acquired as a result
thereof are "general customer", "short sentence", and "anger".
[0284] In this manner, in addition to recognizing the voice that is
voice input as text to process the meaning of transmitted
information by the filters similar to Examples 1 and 2, an analysis
on feeling can be conducted on the basis of the volume and length
of sentence thereof in the case of voice input. Namely, the
censorship control command which gives a reply while taking a
modest attitude can be output as the censorship control command to
the main system if an individual person gets angry, and the
censorship control command for addressing the customer as being
problematic aside from addressing the anger can be output in the
case of a problematic customer who is frequently addressed in much
the same way. Therefore, addressing in accordance with the
censorship control command makes it possible for anybody to easily
resolve the problem.
[0285] <<Other Aspect>>
[0286] Furthermore, according to the present invention, it is also
possible to provide the censorship system or censorship function
which takes note of individual preference information which has
been often left untreated in the field of censorship, and
establishes a technique for organizing the expression contents
thereof as the property in the field of censorship so as to be
connected to the individual service of the main system.
[0287] Furthermore, according to the present invention, in the
artificial intelligence system which answers questions from users,
the artificial intelligence system is connected with the censorship
system or censorship function described above, so that it is also
possible to provide the artificial intelligence system which
answers questions reflecting the preference information existing in
the field of censorship.
[0288] An information processing system according to another aspect
of the present invention can be provided with:
[0289] a field-of-censorship generation device for decomposing
individual person generated data generated by many individual
persons who take part in the main system into a plurality of
decomposed data that can identify the meaning thereof, extracting
data that satisfies both a predetermined relation condition
characterized for each community regarding an object indicated by
each of the decomposed data and a predetermined characteristic
condition characterized for each community regarding the object,
and generating a collection of first extracted data extracted
thereby as a field of censorship; and
[0290] a device for making particularity available for extracting
data that satisfies a particularity condition characterized for
each community indicating a predetermined particularity in
connection with the object from the collection of the first
extracted data, and detecting the predetermined particularity from
second extracted data extracted thereby to make it available.
[0291] Furthermore, in "decomposing individual person generated
data generated by an individual person into a plurality of
decomposed data that can identify the meaning, extracting data that
satisfies both a predetermined relation condition characterized for
each community regarding an object indicated by each of the
decomposed data and a predetermined characteristic condition
characterized for each community regarding the object" described
above, the text data is employed as a linchpin data format as the
data that can identify the meaning, as described in the
aforementioned embodiments of the present invention. However, if
other data formats that can identify the meaning appears instead of
the text data in future, those data formats can be applied to the
present invention.
[0292] In this manner, the present invention is not limited to the
text data. The case where the text data is employed is, however, as
follows. Specifically, the information processing system according
to another aspect of the present invention can be one which is
provided with:
[0293] a field-of-censorship generation device for decomposing text
data based on individual person generated data generated by an
individual person into decomposed data that can identify the
meaning, extracting data that satisfies both a predetermined
relation condition characterized for each community regarding an
object indicated by the decomposed text data and a predetermined
characteristic condition characterized for each community regarding
the object, and generating a collection of first extracted data
extracted thereby as a field of censorship;
[0294] a device for making particularity available for extracting
data that satisfies a particular condition indicating a
predetermined particularity characterized for each community
regarding the object from the collection of the first extracted
data, and detecting the predetermined particularity from second
extracted data extracted thereby to make it available; and
[0295] a monitoring device for determining an individual person to
be monitored and the contents of monitoring for controlling the
monitoring based on the second extracted data.
EXPLANATION OF REFERENCE NUMERALS
[0296] 10 Network [0297] 20 Server [0298] 100 Monitoring system,
censorship system, preference availability system
* * * * *