U.S. patent application number 09/771742 was filed with the patent office on 2001-06-28 for intelligent networked information sharing.
Invention is credited to Wachtel, Edward I..
Application Number | 20010005847 09/771742 |
Document ID | / |
Family ID | 26676164 |
Filed Date | 2001-06-28 |
United States Patent
Application |
20010005847 |
Kind Code |
A1 |
Wachtel, Edward I. |
June 28, 2001 |
Intelligent networked information sharing
Abstract
A networked information sharing model is described. The network
described comprises a client-server model or a client only model.
There exists a shared information database, a shared category
database, a shared interest profile database and a shared client
enhancement database, each of which is continually and dynamically
updated. The shared category database contains categories of
interests, within which are weighted and marked information units.
Weights are arrived at by empirical use. Marks are maintained to
distinguish where the information came from and to access
information according to client source preference. The shared
interest profile contains a set of profiles which clients are
associated with. Useful client categories within profiles are
offered when requested. A shared client enhancement list is
maintained to identify and weight useful sources of information. A
client specific database is maintained with client categories,
preferred information sources, weights and weighted information
access history. This database is used in conjunction with the
shared databases to provide intelligent information sharing.
Inventors: |
Wachtel, Edward I.; (New
York, NY) |
Correspondence
Address: |
Craig E. Shinners
Law Office of Craig E. Shinners
Suite 610
301 East Colorado Blvd.
Pasadena
CA
91101
US
|
Family ID: |
26676164 |
Appl. No.: |
09/771742 |
Filed: |
January 29, 2001 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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09771742 |
Jan 29, 2001 |
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08751613 |
Nov 18, 1996 |
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6195654 |
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60006863 |
Nov 16, 1995 |
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Current U.S.
Class: |
1/1 ;
707/999.001; 707/E17.109; 707/E17.111 |
Current CPC
Class: |
Y10S 707/99932 20130101;
G06F 16/9535 20190101; Y10S 707/99933 20130101; Y10S 707/99935
20130101; G06F 16/954 20190101 |
Class at
Publication: |
707/1 |
International
Class: |
G06F 007/00 |
Claims
What is claimed is:
1. A method for sharing information on a network of computers which
are interconnected by communication hardware and software
comprising: information units to be shared; clients which use said
network of computers to offer and/or access said information units;
a shared database containing shared information units; dynamically
weighting means for said information units according to the utility
of said information units to said clients; offering means by said
client of information units to said shared database containing
shared information units; offering means to said clients of said
information units from said shared database based on the weight of
said information units; whereby clients can obtain information of
utility without searching through databases of information lacking
utility.
2. The method of claim 1 whereby shared databases are located on
the server and databases pertaining to the client only are located
on the client.
3. The method of claim 1 further including a set of interest
categories maintained per client which is a subset of a shared
interest categories database, said information units being assigned
to said shared information categories, whereby said accessing means
and offering means of assigned information units occurs after the
category has been selected.
4. The method of claim 3 further including a shared interest
profile database whereby clients have client identifiers whereby
profile client identifier means exist whereby client identifiers
are assigned to said interest profiles according to the closest
match to their individual set of interest categories.
5. The method of claim 4 further including a category profile
offering means of new categories to clients based on the use and
utility of other categories used by different clients in the same
interest profile.
6. The method of claim 4 further including an information units
profile offering means of new information units to clients based on
the use and utility of other information units used by different
clients in the same interest profile.
7. The method of claim 3 further including a category utility
weight which indicates the use and utility of a given category and
is dynamically updated with use and lack of use.
8. The method of claim 7 further including a category removal means
whereby categories of little use are remove from the client said
set of information categories.
9. The method of claim 1 wherein said weighting means is determined
by the number of accesses by clients and feedback from client
utility ratings.
10. The method of claim 1 further including a shared client
enhancement list database which maintains a list of clients and a
weight designating the amount of useful information units offered
to said shared database of information units.
11. The method of claim 10 further including a server time-slice
allocation means based on said shared enhancement list database
weight for that client and the processing bandwidth available on
the server.
12. The method of claim 10 further including a posting requests
means whereby a server database can be accessed directly by a
client or a client can post a request for an information unit
within the database, whereby a client which supplies useful
information units to posted requests gains a higher weight in said
shared enhancement list.
13. The method of claim 10 further including an information
acceptance means whereby weights in said shared enhancement list
database are used to determine whether an information unit offered
by the client will be stored on said shared database of information
units and if so, what initial weight will be given to the offered
information unit.
14. The method of claim 1 further including an information units
accessed database per client which will be dynamically updated as
clients access new said information units, with a method to attach
to that new said information unit, whereby said information units
accessed database will be used to add information to said shared
database of information units.
15. The method of claim 1 whereby information units are assigned
said client identifier which identifies the client who offered the
information.
16. The method of claim 15 further including a preferred
information client identifiers list per client whereby a preferred
client access means is used to access information from said shared
database of information units based on clients which previously
have supplied information units of utility.
17. The method of claim 15 further including a not preferred
information client identifiers list per client whereby a not
preferred client access means is used to access information from
said shared database of information units based on clients which
previously have supplied information units without utility.
18. The method of claim 1 whereby shared databases are distributed
across one or more clients and databases pertaining to the client
only are located on the client.
19. The method of claim 18 further including client only processing
means whereby processing involving interactive access to a shared
database is accomplished by any client and processing pertaining to
the client only is completed by the client.
20. The method of claim 2 further including client-server
processing means whereby processing involving interactive access to
a shared database is completed by the server and processing
pertaining to the client only is completed by the client.
Description
[0001] This application claims the benefit of prior provisional
application Ser. No. 60/006,863, filed on Nov. 16, 1995.
BACKGROUND
[0002] 1. Field of the Invention
[0003] This invention relates to computer systems and in particular
to an intelligent means of acquiring, storing and sharing
information.
[0004] 2. Description of Prior Art
[0005]
[0006] Servers on the Internet contain vast quantities of
information and are distributed around the globe. However, the vast
majority of information is of no use to a particular person.
Finding information of use requires considerable knowledge as well
as time and money. Mosaic offers a graphical user interface to the
Internet making access easier. Yet there are tens of thousands of
servers to choose from and a large quantity of information to sift
through once on an individual server. Furthermore, the server is
usually slow due to the number of persons logged onto it and by the
network traffic to communicate with it.
[0007] There are librarian servers on the Internet which scan
thousands of servers and catalogue the files on the servers.
However, these librarian servers are slow due to the magnitude of
the search and the large number of requesters. Further, one may
find hundreds of potential files on a given topic; accessing and
reading the files to find useful ones takes and wastes considerable
time. These servers may cover some topics to a considerable degree
and others sparsely.
[0008] Services such as CompuServe and America Online alleviate
congestion problems to a considerable degree by charging money.
However, since the on-line service is charging per minute, one may
not have the time to sift through on-line services and bulletin
boards to find what one is looking for. The on-line service reduces
the vast quantities of useless information on the Internet by
offering a smaller set of services and bulletin boards found to be
of interest to most people. However, the list of services is still
very large and one is not confident which if any will be of
interest. Furthermore, excellent information may be available on
the Internet or elsewhere which the particular on-line service does
not offer.
[0009] Bulletin boards may haphazardly provide specific information
of interest. However, one must sift through answers which may or
may not be of interest. Furthermore, one must find the bulletin
board of interest; on the Internet there are a vast number which
may or may not suit a person.
[0010] Expert systems are available which sift through information
by use of algorithms, driven by rules and stored in a knowledge
base. However, expert systems are expensive and time consuming to
produce and maintain. It would be impossible to cover the vast and
evolving information located on the Internet. Furthermore, the
processing time required to run the expert systems would reduce the
response time of these already slow servers considerably.
[0011] Another option is an heuristic database weighted by the
usefulness response of clients. U.S. Pat. No. 5,301,314 to Gifford
(1991) describes this method. The method consists of placing
information which was determined useful within a category higher on
the tree of offered information within the category. This method
falls short in several ways. First, one must sift through the
categories. Second, once in the category, one must sift through
excellent answers until one finds the excellent answer which
matches the question; the answer may not even be on the database or
may be located in a different category. Third, people differ. In a
category of movies, as an example, an excellent choice for an
English Professor may be a poor choice to an engineer. Forth, what
if one is not sure what categories may be of interest. There are
millions on the Internet and thousands in subscriber services which
may or may not suit a given person.
[0012] Another option is to provide trained personnel to search for
information. This solution is expensive. Further, what is a good
information to the personnel may not be to the person requesting
the information. If the question is highly specialized in a given
field, the personnel may not have the technical knowledge to find
the appropriate information. Finally, searching even by a trained
person, takes a considerable amount of time.
[0013] An intelligent computer based method to share information is
needed which will reduce traffic on a networked system of computers
and processing load on server machines. This method should offer
the best information for a particular persons needs, whether that
information is located locally on the server, is located on the
Internet or is chosen from a set of responses on a bulletin
board.
OBJECTS AND ADVANTAGES
[0014] It is, therefore, an object of the invention to provide a
method of sharing information between client computers which will
decrease the traffic on a network and decrease the load on a server
machine.
[0015] It is another object of the invention for the server
computer or the client computer to choose information which will
optimally best serve the particular client's need.
[0016] It is another object of the invention to gather information
from the Internet or other sources which will be of future value to
clients and keep a database of that information or pointers to that
information.
[0017] It is another object of the invention to provide an
effective method of offering topics of interest to clients on an
individual basis.
[0018] Still further objects and advantages will become apparent
from a consideration of the ensuing description and accompanying
drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] FIG. 1 shows a network of computers consisting of clients
and servers which will share information.
[0020] FIG. 2 shows a client interface to the interest
categories.
[0021] FIG. 3 shows the structure of an information unit.
[0022] FIG. 4 shows the client database with an interest category
and an information units accessed area
[0023] FIG. 5 shows the networked information sharing model.
[0024] FIG. 6 shows the recording of an information access by a
client
[0025] FIG. 7 shows the upload and processing of client information
to a server.
[0026] FIG. 8 shows a method of calculating a client information
weight.
[0027] FIG. 9 shows a method of weighting information used by
clients from a server.
[0028] FIG. 10 is a model showing the intelligent retrieval of
requested information.
[0029] FIG. 11 is a model for a database which can be searched in
or posted to for information.
[0030] FIG. 12 shows the intelligent update of a client category
list on the client database.
[0031] FIG. 13 shows the intelligent update of the server interest
profile list and the intelligent offer of new categories.
[0032] FIG. 14 shows a networked information sharing model
consisting only of clients.
SUMMARY
[0033] A networked information sharing model is described
comprising a client-server model or a client only model where there
exists a shared information database, a shared category database, a
shared interest profile database and a shared client enhancement
database, each of which is continually and dynamically updated, the
shared category database containing categories of interests, within
which are weighted and marked information units, weights arrived at
by empirical use and marks maintained to distinguish where the
information came from and to access information according to client
source preference. The shared interest profile contains a set of
profiles which clients are associated with whereby useful client
categories within profiles are offered when requested, a shared
client enhancement list maintained to identify and weight useful
sources of information and a client specific database maintained
with client categories, preferred information sources, weights and
weighted information access history whereby this database is used
in conjunction with the shared databases to provide intelligent
information sharing.
PREFERRED EMBODIMENT--DESCRIPTION
[0034] FIG. 1 shows the preferred network structure of the
invention. This consists of a set of clients who will share
information over a communications link 26. There is a client
database 28 containing a client index of interest categories and
associated category choice information. There is one or more
servers which contain a complete set of interest categories in the
form of a complete category database 18. The interest category
client database 28 is a subset of the complete category database
18. Server information database 20 consists of information or
pointers to information. Information units pointing to information
in server database 20 are kept for each category stored in complete
category database 18. There is an interest profile database 32
containing a full set of interest profiles. Each client on the
information network is assigned to one or more interest profiles.
There is a client database enhancement list 30. This list contains
each client and a number representing the amount of useful
information from this client which was useful to other clients.
[0035] This invention offers a method of intelligently offering and
deleting categories from interest client database 28, intelligently
offering information within an interest category from information
database 20 and judiciously gathering information for information
database 20 for categories in complete category database 18. The
following examples will clarify these activities.
[0036] As one example, client database 28 for client 22 may contain
bulletin board interest categories of baseball player statistics,
baseball game statistics and articles on current baseball teams.
Another category may be offered to client 22 from server 24 of
baseball stadium statistics. The decision to offer the category of
baseball stadium statistics will be determined by artificial
intelligence.
[0037] As another example, if a request for a prediction of what
will occur in the next Yankee game is posted to the baseball game
statistics interest category by client 22 which is run by server
24, server 24 may return a list of bulletin board answers
prioritized based on which answer will most probably be best for
client 22. The method by which server 24 prioritizes the answers
for client 22 will occur without human intervention.
[0038] As another example, server 24 may judiciously gather
pointers off the Internet of interesting articles on current
baseball teams and store the pointers in information database 20
for the current baseball teams category located in complete
category database 18. Client 22A may request three articles from
the database. server 24 would offer what it thinks is the best two
articles for client 22A. Again, the gathering of information and
the offering occurs without human intervention.
[0039] FIG. 2 shows a user interface for current interest
categories 36 and suggested interest categories 34. Each interest
category is a node of an interest category tree. Child expanded
node 38 shows node 3 with one level of children. If a client
decides to get more specific than his assigned category he can view
below the category. Parent expanded node 40 shows node 3 with two
levels of parent nodes. If the client would like to view the more
general categories above his assigned category he can view above
his assigned category. As an example, node 3 may be backgammon. The
three children of node 3 may be rules of backgammon, great
backgammon players and backgammon strategy. The parents of
backgammon may be board games and the grandparent may be leisure
activities. The client may be assigned the backgammon node and may
choose to view what categories are above or below him.
[0040] The information database 20 of FIG. 1 is located on the
server. It consists of information units, as shown in FIG. 3,
containing an information access area 50 to access the information.
The information may be located locally on the server or may be
located remotely. Remote location can be anywhere outside of the
given server. It contains a global information unit index 44 used
by the client and the server to identify an information unit. It
contains usefulness weights 46 which identify the usefulness of the
information unit, access counts 48 which record the number of times
the information unit has been accessed and an information access
area 50 which is a method to get to the information or a pointer to
a method to get to the information. The client fills these areas as
he uses the information unit. The server accumulates client values
and combines them to produce server values which are then stored in
the information unit. There can be more than one count or weight
since an information unit will have records of counts and weights
for the given piece of information and the categories and server
leading to that piece of information.
[0041] Referring now to FIG. 4, the client database 28A is located
on the client. It contains an ordered list of client interest
categories 58. Information is kept on each category. Indexes of
information accessed 60 reflects information units which have
already been accessed from this category. The category utility
weight 62 is based on use and satisfaction with the use of the
category. Category use count 64 is a count of the number of times
this category has been used. Not preferred information client Ids
66 and preferred information client Ids 68 reflect encrypted Ids of
other clients whose information this client has used. Information
units accessed 80 for this category reflect all information
accessed within the past arbitrary period of time (for example the
past month). These units are given to the server for potential use
by other clients. Profile numbers 81 associate this client with the
interest profile database 32 of FIG. 1. Previously rejected
categories 82 are maintained to be given to the server before
requesting new categories of interest to this client.
[0042] By use of these structures an intelligent information
sharing system is built across a network. The interaction between
these structures allows for the transfer of useful information to
meet a particular clients interests and needs.
PREFERRED EMBODIMENT--OPERATION
[0043] The networked information sharing model is shown in FIG. 5.
Objects described in FIGS. 1, 2, 3 and 4 will be referenced here
and in subsequent paragraphs. In step 84 the shared information
database 20 of FIG. 1 and the shared complete category database 18
of FIG. 1 are populated with information and cross references to
that information. In step 86 client interest categories 58 of FIG.
4, which together are one profile, are assigned to each client;
this profile of categories is matched to one or more generic
profiles in shared interest profile database 32 of FIG. 1. In step
88 clients are watched by the client machine; referring to FIG. 4,
information on server destinations 78, information items 74 and
categories chosen 76 are recorded on the client database 28A in the
Information Units Accessed 80 table. In step 90 information and
destinations accessed by the client are recorded with usefulness
weights 46 of FIG. 3 and access counts 48 of FIG. 3 within each
information unit on the server in shared complete category database
18 of FIG. 1. In step 92 the clients interest category profile
assignments in shared interest profile database 32 of FIG. 1 are
updated according to the current category profile information
recorded in step 88. The client requests specific pieces of
information, server or database destinations and new categories in
step 94; with the shared interest profile database 32 of FIG. 1
updated in step 92 and the analysis done in step 90, data is
returned to the client.
[0044] Referring back to FIG. 1, the server information database 20
and the complete category database 18 is initially populated by
standard information collection. On-line services have category
directories and information databases. Many books can be found with
categorized directories of on-line services. Thus, we begin with a
good base of information database 20 cross referenced through
complete category database 18. The complete category database 18
contains leaf nodes and non leaf nodes, each representing an
interest category. Clients will be assigned to interest category
nodes. Referring now to FIG. 4, this information will be kept in
the client database 28A as client interest categories 58. Clients
will also be assigned a set of profile numbers 81 which will
associate them with interest profiles located in the interest
profile database 32 of FIG. 1. Profiles and interest categories
will be initially assigned by use of an interest survey prepared by
a marketing and/or psychology group. Subgroups within an interest
category can be formed where interest in information within a
category will differ substantially between one client and another.
Subsequent updates will be made dynamically by the intelligence
within the client and server computers as described below.
[0045] The client machine watches where the client goes to access
information and what information he accesses. Privacy is of course
imperative. Perhaps, the client can turn on or off the watch
facility by pressing a button on the display. The client would also
have an encrypted and private client ID. Perhaps, at the end of an
information search the client can press a share button to allow the
sharing of the information with other clients.
[0046] A script is kept which when launched leads to the
information. The computer keeps track of how often the information
site and the nodes leading to the information site is accessed; it
prompts the user at the end of the information for a usefulness
weight from excellent to poor. The computer keeps track of how
often each point leading to the final information is accessed. The
script leading to the information in the information access area 50
of FIG. 3, the access counts 48 of FIG. 3 and the usefulness
weights 46 of FIG. 3 are kept within the information unit structure
which is passed between client database 28A of FIG. 4 and server
complete category database 18 of FIG. 1. These information units
point to the information database 20 of FIG. 1 through the
information access area 50 of FIG. 3.
[0047] FIG. 6 details the process of recording information access
by a client. Let us call this client Client A. In step 96 client A
accesses an information server, as an example the Hall of Malls
server; in step 98 the client computer increments the count of how
often client A has accessed the Hall of Malls server. In step 100
the client selects a category, as an example the Florida Mall; the
computer increments the count for Florida Mall for client A in step
102. Client A goes to The Unusual Music Store subcategory in step
104; the computer increments the count for The Unusual Music Store
in step 106. In step 108 the client chooses a resource, in this
example a tape called The Nightfly; the computer increments the
count for this resource, the Nightfly tape, in step 110. In step
112 the client rates each node in this access: the Hall of Malls,
the Florida Mall, the Unusual Music Store and The Nightfly. The
client computer records this information in the usefulness weights
46 of FIG. 3 and access counts 48 of FIG. 3 of the information unit
index 44 of FIG. 3.
[0048] If client A has a history of giving good information to
other clients, then the information unit is recorded by the server.
FIG. 7 details this method. In step 114 the client connects to the
server. In step 116 the server accesses the client usefulness index
from enhancement database 30. This index is an historic measurement
of how useful information offered by this client has been to other
clients; it is based on the number of users accessing the
information who were satisfied with the information. In step 118
the server requests information from the client which has a use
count above a particular number and/or a rating above a particular
number; the count and rating number are lower for a high client
usefulness index and higher for a low client usefulness index. In
step 120 the client sends the server the information with counts
and ratings. In step 122 the client records this information as
sent; subsequent uploads will only resend this information if
counts or ratings have changed substantially and will only send the
deltas of the information. In step 124 the server records the
information unit within an ordered weighted list.
[0049] FIG. 8 gives a method for weighting information received by
a client. It uses a rating index of 1, 2 or 3. This method is for
information which has a count greater than or equal to one, as an
example the Hall of Malls destination information unit. In step 126
the information with a use count is received. If, in step 128, the
rating is 1 (the top rating) then in step 130, the weight is
assigned two times the count. If, in step 132, the rating is 2 then
in step 134 the weight is assigned 1.7 times the count. If, in step
136, the rating is 3 then in step 138 the weight is assigned 1.5
times the count. If, in step 140, there is no rating then the
weight is assigned 1.7 times the count. In step 142 the weight is
assigned whatever the current weight is times the client data
usefulness index. This method takes into account three factors: the
historic usefulness of the clients data, the number of times the
data was reused and the rated satisfaction when using the
information.
[0050] Referring back to FIG. 1, If the information is accessed
through a category in complete category database 18, the
information is shared with clients in this category. If the
information was not accessed through a category it can be offered
to clients with a similar interest profile accessed from the
interest profile database 32; if the information is not categorized
and turns out to be useful to a number of clients, a question can
be asked of each client as to which category it belongs in. If one
or more categories consistently comes up, the information unit can
be placed for access within a given category. Otherwise the
information can be placed in a catch all generic category.
[0051] FIG. 9 gives a method for keeping a dynamic and a static
utility count for a given piece of information received by a server
from a client. In step 144 the information is tried by a client.
If, in step 146, the information is rated as 7 or more on a 1 to 10
scale then in step 148 the new dynamic count is assigned the old
current dynamic count plus the utility rating squared; the static
count in step 150 is likewise updated. The static count gives total
utility of this item since its inception. The dynamic utility count
gives a current utility weight. This is done by reducing the past
utility weight with time, thus requiring continual usefulness of
the information. In step 154, if the date is the first of the
month, then in step 156 the dynamic count weight is reduced by a
factor of 0.3, otherwise no action is taken 158.
[0052] The same type of method can be used to continually populate
a bulletin board containing baseball articles. Users would offer
interesting articles. The information stored in server information
database 20 of FIG. 1 would contain a pointer to the article on the
Internet or in the service provider database. An information unit
pointing to the information in information database 20 of FIG. 1
would be kept in the baseball articles category in complete
category database 18 of FIG. 1. Access counts 48 of FIG. 3 and
usefulness weights 46 of FIG. 3 of each article would be kept in
the corresponding information units. The enhancement database 30 of
FIG. 1 is kept up to date with the private user ID, the category if
any and the information offered counts.
[0053] Referring back to FIG. 4, the client database 28A contains
the client interest categories 58. Beneath a given category, there
is a preferred information client IDs 68 and a not preferred
information client IDs 66 containing encrypted, private Ids of
other clients whose information was useful. From this list the
server chooses articles to offer by finding offered articles from
clients who are on the preferred information client IDs 68. FIG. 10
demonstrates this method. In step 160 the client requests
information from a category. In step 162 the client sends indexes
of information already accessed 60 of FIG. 4. In step 164 the
client sends encrypted preferred information client IDs 68 of FIG.
4 of historically preferred providers and those providers who were
not preferred information client IDs 66 of FIG. 4. If, in step 166,
if information is available from a preferred provider, if there is
no higher weighted information from a new provider in step 170,
then in step 172 the preferred provider information is sent to the
client. If, in step 170 there is higher weighted information from a
new provider, if, in step 174 new provider information has been
sent within the last three accesses, then in step 172 the preferred
provider information is sent to the client. If, in step 174, new
information has not been sent within the last three accesses, then
in step 168 the information from the new provider is sent to the
client. This method offers information from historically useful
providers for this client. This method distinguishes between
clients within a category. This becomes particularly useful where
there is a range of tastes within a category, for example with
movies, magazines, restaurants and music. The method also provides
for sampling new providers as seen in step 174.
[0054] Where there is a large database which is heavily used, the
enhancement database 30 of FIG. 1 and the local preferred
information client IDs 68 of FIG. 4 can be used effectively. As an
example, the Archie server is a librarian for the Internet and can
be searched for sources. By adding a bulletin board, users can post
questions or search for them. Clients who answer the most posted
questions with the least average search time can be given more time
slices on the Archie server. Thus, slow and or inexperienced Archie
users do not waste time on the server. Furthermore, they receive
sources which may well be better than if they had searched Archie.
Further, rather than a huge list which must be transferred over the
Internet, a potentially small list is returned via the bulletin
board. Thus, the server load is reduced and users get quality
information.
[0055] FIG. 11 gives a method for a bulletin board and database
which can be searched. If client A posts a request in step 176 and
an answer is given back by client B in step 178 then if in step 180
Client A rates the information as 7 or more in utility then the
client B answer count is incremented by the Client A utility rating
squared in step 182. If client B chooses not to post a question in
step 176 then, in step 184, he is given a timeslice equal to the
minimum timeslice unit times his search master multiplier. The
search master multiplier is determined by the current load on the
server and client Bs client answer count. In step 186 the search
begins.
[0056] Referring now back to FIG. 1, the interest profile database
32 is dynamically updated according to the client interest
categories 58 of FIG. 4 and their associated category utility
weight 62 of FIG. 4 contained in the client database 28A of FIG. 4.
Thus, a client which was placed in sports and music categories may
become engrossed in an accounting job requiring information about
the economy and stocks; he may, therefore, become associated to a
different set of interest profile categories in interest profile
database 32.
[0057] FIG. 12 offers a method of dynamically updating client
interest categories 58 of FIG. 4. In step 176 information is used
in an interest category. In step 178 the interest category count 64
of FIG. 4 is incremented by 1. If the user is exiting from the
service provider in step 180, if in step 182 the user has been on
the network a given number of hours K (for example 40 hours) since
last updating his interest category profile then in step 184 his
interest category profile on client database 28A of FIG. 4 is
updated. For all categories which have not been checked in K hours
of on-line use, the interest category count 64 of FIG. 4 is reduced
by a factor of 0.3. In step 186, if the number of interest
categories is greater than a given constant J (for example 20),
categories are removed from the current interests category 36 of
FIG. 2 directory with an interest count less than a given number L
(for example 20 for a scale between 0 and 100) in step 188; perhaps
removed categories are placed in an unused interest category
directory for subsequent purging by the client. In step 190 the
category weight change Boolean 70 of FIG. 4 is set to TRUE. This
value will be used by the server to update the client on interest
profile database 32 of FIG. 1. This method provides a dynamically
updated client interest profile.
[0058] The profile directory is particularly useful in offering new
categories of interest. By noting categories not on Client A but
often used by other clients within the interest profile, offers can
be made to client A of new categories he has not tried. Not
categorized but new and enjoyable services used by members in the
interest profile can be offered to clients as well.
[0059] FIG. 13 demonstrates a method of offering categories and
services based on an interest profile. In step 192 the client
connects to the service provider. In step 194, the client interest
categories 58 of FIG. 4 of the client database 28A of FIG. 4 is
retrieved. In step 196, if the category weight change Boolean 70 of
FIG. 4 is TRUE, in step 198 the server interest profile database 32
of FIG. 1 is updated to identify the client with the closest
interest profiles on the server. In step 200, if there is a request
for a new category, then in step 202 the client sends previously
rejected categories 82 of FIG. 4. In step 204 the client is sent an
ordered list of not rejected, most used and enjoyed categories
within his interest profile database 32 of FIG. 1. If the client
explicitly rejects a category in step 204, then in step 206 this is
recorded in his local client database 28A of FIG. 1. In step 210
the client adds any categories he would like to try. Likewise,
specific services can be offered to a client based on other clients
within his interest profile database 32 of FIG. 1. This offers the
client a simple and effective method of acquiring new information
and categories of interest.
[0060] Thus, a method using machine based intelligence to share
information and interests over a network of computers has been
described. The method includes client databases of interests and
information and processing of that data. The benefits include
information retrieval specific to a clients needs, reduced traffic
and CPU time for searching databases, client information stored on
client machines reducing nonvolatile disk memory requirements on
the server, client preprocessing on client machines reducing the
cost of analyzing and distributing information on the server and
interactive useful information storage in locations where
intelligence exists to distribute that information.
[0061] While the invention has been illustrated in connection with
a preferred embodiment, it should be understood that many
variations will occur to those of ordinary skill in the art, and
that the scope of the invention is defined only by the claims
appended hereto and equivalent.
OTHER EMBODIMENTS
Client Information Sharing Without a Server--Description
[0062] FIG. 14 shows an alternate network structure of the
invention. This consists of a set of clients who will share
information over a communications link 12A without a server. There
is a client database 14B containing a client index of interest
categories and associated category choice information. There is a
unique client database 14B on each client. There is a client shared
database containing a complete set of interest categories in the
form of a complete category database 18A. The database can be
mirrored on several clients and can be distributed over a number of
clients. At least one full copy of the database should be
accessible to all other clients at all times. The interest category
client database 14B is a subset of the complete category database
18A. Information database 20A is shared by all clients and consists
of information or pointers to information for each category stored
in complete category database 18A. Information database 20A can be
mirrored and distributed across a number of clients. One full copy
should be accessible at all times. The interest profile database
32A and client database enhancement list 30A is likewise a shared
client database and can be mirrored and distributed. One full copy
should be accessible at all times.
[0063] Processing formally done by the server is now done by each
client using the shared complete category database 18A and the
shared information database 20A.
Client Information Sharing Without a Server--Operation
[0064] The networked information sharing model is shown in FIG. 5.
Objects described in FIGS. 14, 2 and 4 will be referenced in this
discussion. Referring to FIG. 5, in step 84 the shared information
database 20A of FIG. 14 and the shared complete category database
18A of FIG. 14 are populated with information and cross references
to that information. In step 86 client interest categories 82 of
FIG. 4, which together are one profile, are assigned to each
client; this profile of categories is matched to one or more
generic profiles in shared interest profile database 32A of FIG.
14. In step 88 clients are watched by the client machine; referring
to FIG. 4, information on server destinations 78, information items
74 and categories chosen 76 are recorded on the client database 14A
in the Information Units Accessed 58 table. In step 90 information
and destinations accessed by the client are recorded with
usefulness weights 46 of FIG. 2 and access counts 48 of FIG. 2
within each information unit on the server in shared complete
category database 18A of FIG. 14. In step 92 the clients interest
category profile assignments in shared interest profile database
32A of FIG. 14 are updated according to the current category
profile information recorded in step 88. The client requests
specific pieces of information, server or database destinations and
new categories in step 94; with the shared interest profile
database 32A of FIG. 14 updated in step 92 and the analysis done in
step 90, data is returned to the client.
[0065] Actions taken by the server in the preferred embodiment are
now implemented by the client.
CONCLUSIONS, RAMIFICATIONS, AND SCOPE
[0066] Accordingly, it can be seen that a networked information
sharing system can intelligently distribute and gather information
for a group of clients. Clients have a wide range of interests and
skill levels. By dividing clients into category profiles and
dynamically matching clients to sources of information, high
quality information sharing is achieved. An intelligent means of
information sharing can grow the skills, productivity and personal
interests of clients. In addition, by filtering less useful
information and obviating slow and massive searches, the percentage
of useful information flowing across the bandwidth of the network
increases. By offering information to the client rather than
necessitating the client to search for himself, clients without
computer expertise can enjoy and benefit from the advantages of
information distributed across a disperse network of servers.
[0067] Although the description above contains many specificities,
these should not be construed as limiting the scope of the
invention but as merely providing illustrations of some of the
presently preferred embodiments of this invention. Various other
embodiments and ramifications are possible within it's scope.
[0068] Thus the scope of the invention should be determined by the
appended claims and their legal equivalents, rather than by the
examples given.
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