U.S. patent application number 14/791140 was filed with the patent office on 2015-10-29 for system and method for determining similarities between online entities.
The applicant listed for this patent is Megathread Ltd.. Invention is credited to BRIAN ASSAM.
Application Number | 20150310059 14/791140 |
Document ID | / |
Family ID | 48611267 |
Filed Date | 2015-10-29 |
United States Patent
Application |
20150310059 |
Kind Code |
A1 |
ASSAM; BRIAN |
October 29, 2015 |
SYSTEM AND METHOD FOR DETERMINING SIMILARITIES BETWEEN ONLINE
ENTITIES
Abstract
Provided are a system and method to determine similarities. The
method includes gathering metadata from at least one posting by a
First User on a first Social Network to define at least one First
Field associated with at least one First Entity, each associated
First Field having a value. The method evaluates responses to the
posting by at least one Third Party, and in response to the Third
Party using one or more of the First Fields, increments the value
of each used First Field. An indication of the values of each First
Field associated with each First Entity is provided, the indicated
values permitting a determination of similarity to at least one
Second Entity. An associated system for determining similarity is
also disclosed
Inventors: |
ASSAM; BRIAN; (Sioux Falls,
ND) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Megathread Ltd. |
Sioux Falls |
SD |
US |
|
|
Family ID: |
48611267 |
Appl. No.: |
14/791140 |
Filed: |
July 2, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13709189 |
Dec 10, 2012 |
9135291 |
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14791140 |
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61570606 |
Dec 14, 2011 |
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Current U.S.
Class: |
707/748 |
Current CPC
Class: |
G06Q 50/01 20130101;
G06F 16/24 20190101; G06F 16/31 20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A method to determine similarities between online Entities on at
least one Social Network comprising for each entity: establishing a
Database of Fields collected from at least one historical
discussion on a first Social Network, the Discussion including at
least one posting by a first user providing at least one text first
field associated with at least a First Entity, and a plurality of
response posting by at least one second user; defining an automated
value to be assigned to each associated field upon subsequent use
in a response by a second user; evaluating second user responses to
the posting by the first user, and in response to the second user
using one or more of the first fields, applying the automated value
to aggregate the value of each first field used in the response,
wherein the second user is different from the first user; and
evaluating the aggregated value of each first field to one another
to establish a first table providing a context of association
between first fields to identify the First Entity as having a
quantified level of interest as identified by each first field, the
aggregated value permitting a determination of credibility for
similarity to at least one Second Entity.
2. The method of claim 1, wherein the method is performed
substantially concurrently with new postings and responses
regarding the historical discussion.
3. The method of claim 1, wherein the First Entity is a Social
Media Object.
4. The method of claim 1, wherein providing an indication of the
aggregated value of each first field includes evaluating the
aggregated value of each field to one another to establish a table
providing a context of association between fields to identify the
first entity as value of a second Field.
5. The method of claim 4, wherein the First Entity may range from a
low order entity to a high order entity, the table of a high order
entity including at least one table of a low order entity having a
quantified level of interest as identified by each Field.
6. The method of claim 1, wherein at least a subset of associated
First Fields are First Entities associated to other First Fields as
Second Entities, the association between First Fields providing a
context of association as between the associated Fields
7. The method of claim 1, wherein the Second Entity is selected
from the group consisting of, a Second User, at least one Field, a
Posting by the Second User, the First Social Network, a Second
Social Network, the First Discussion, a Social Media Object, a
Second Discussion, an interest.
8. The method of claim 6, wherein the Second Entity has an
established Table providing a context of associations between
Fields to identify the Second Entity as having a quantified level
of interest as identified by each Field.
9. The method of claim 8, wherein the Second Entity may range from
a low order entity to a high order entity, the table of a high
order entity including at least one table of a low order
entity.
10. The method of claim 1, wherein the method is performed
substantially concurrently with new postings and responses
regarding the historical discussion.
11. The method of claim 1, wherein the historical discussion is one
that has previously evolved on the social network.
12. The method of claim 1, wherein the value of the associated
field developed by subsequent use is dissipated over time.
13. The method of claim 1, further including at least a first
automated value to be assigned to each associated field upon
subsequent use in a direct response by a Second User and at least a
second automated value to be assigned to each associated field upon
subsequent use in an indirect response by a Second User, the first
automated value being greater than the second automated value.
14. A non-transitory machine readable medium having recorded
thereon computer implanted instructions for performing the method
of claim 1.
15. A computer system having at least one physical processor and
memory adapted to perform the method of claim 1.
16. A method to determine similarities between online Entities on
at least one Social Network comprising: gathering metadata from at
least one posting by a First User on a first Social Network to
define at least one text First Field provided by the at least one
First User and occurring in the at least one posting, the First
Field associated with at least one First Entity, each associated
First Field having an initial system generated value; defining at
least a first automated value to be assigned to each associated
field upon subsequent use in a direct response by a Third Party and
at least a second automated value to be assigned to each associated
field upon subsequent use in an indirect response by a Third Party,
the first automated value being greater than second automated
value; evaluating responses to the posting by at least one third
party different from the first user, and in response to the third
party using one or more of the associated first fields in the
response, applying the first automated value for the response as a
direct response and applying the second automated value for the
response as an indirect response, the first or second automated
values applied to aggregate the value of each associated first
field used in the response; and providing an indication of the
aggregated value of each associated first field associated with
each First Entity as developed by the subsequent use of the
associated field in the evaluated third party postings, the
indicated aggregated value permitting a determination of
credibility for similarity to at least one Second Entity querying
for similarity.
17. The method of claim 16, wherein the automatically generated
value of the associated field developed by subsequent use is
dissipated over time.
18. The method of claim 16, wherein providing an indication of the
aggregated value of each first field includes evaluating the
aggregated value of each field to one another to establish a table
providing a context of association between fields to identify the
First Entity as having a quantified level of interest as identified
by each Field.
19. The method of claim 16, wherein the context of association is
determined by comparing the value of a first Field to the value of
a second Field.
20. The method of claim 16, wherein the First Entity may each from
a low order entity to a high order entity, the table of a high
order entity including at least one table of a low order
entity.
21. The method of claim 16, wherein the First Entity is a Social
Media Object.
22. The method of claim 16, wherein providing an indication of the
aggregated value of each first field includes evaluating the
aggregated value of each field to one another to establish a table
providing a context of association between fields to identify the
first entity as value of a second Field.
23. The method of claim 22, wherein the First Entity may range from
a low order entity to a high order entity, the table of a high
order entity including at least one table of a low order entity
having a quantified level of interest as identified by each
Field.
24. The method of claim 16, wherein at least a subset of associated
First Fields are First Entities associated to other First Fields as
Second Entities, the association between First Fields providing a
context of association as between the associated Fields
25. The method of claim 16, wherein the Second Entity is selected
from the group consisting of, a Second User, at least one Field, a
Posting by the Second User, the First Social Network, a Second
Social Network, the First Discussion, a Social Media Object, a
Second Discussion, an interest.
26. The method of claim 24, wherein the Second Entity has an
established Table providing a context of associations between
Fields to identify the Second Entity as having a quantified level
of interest as identified by each Field.
27. The method of claim 26, wherein the Second Entity may range
from a low order entity to a high order entity, the table of a high
order entity including at least one table of a low order
entity.
28. A computer system having at least one physical processor and
memory adapted to perform the method of claim 16.
29. A non-transitory machine readable medium on which is stored a
computer program for determining similarities between Entities on
at least one Social Network the computer program comprising
instructions which when executed by a computer system having at
least one processor performs the steps of: establishing a Database
of Fields collected from a First Discussion on a first Social
Network, the Discussion including at least one posting by a First
User providing at least one First Fields associated with at least a
First Entity, and a plurality of response posting by at least one
second user; defining an automated value to be assigned to each
associated First Fields upon subsequent use in a response by a
second user; evaluating second user responses to the posting by the
First User, and in response to the Second User using one or more of
the First Fields, applying the automated value to aggregate the
value of each First Fields used in the response, wherein the Second
User is different from the First User; and evaluating the
aggregated value of each First Field to one another to establish a
first table providing a context of association between First Fields
to identify the First Entity as having a quantified level of
interest as identified by each First Field, the aggregated value
permitting a determination of credibility for similarity to at
least one Second Entity.
30. The non-transitory machine readable medium of claim 29, wherein
the value of the associated field developed by subsequent use is
dissipated over time.
31. The non-transitory machine readable medium of claim 29, further
including at least a first automated value to be assigned to each
associated field upon subsequent use in a direct response by a
Second User and at least a second automated value to be assigned to
each associated field upon subsequent use in an indirect response
by a Second User, the first automated value being greater than the
second automated value.
32. The non-transitory machine readable medium of claim 29, wherein
the First Entity is a Social Media Object.
33. The non-transitory machine readable medium of claim 29, wherein
the First Entity is selected from the group consisting of, the
First User, at least one Field, the Posting by the First User, the
First Social Network, a Community, a Second Social Network, a First
Discussion, a Second Discussion, an Interest; and the Second Entity
is selected from the group consisting of, a Second User, at least
one Field, a Posting by the Second User, the First Social Network,
a Second Social Network, the First Discussion, a Social Media
Object, a Second Discussion, an interest.
34. The non-transitory machine readable medium of claim 33, wherein
the each Entity may range from a low order entity to a high order
entity, the table of a high order entity including at least one
table of a low order entity.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation in part of U.S. patent
application Ser. No. 13/709,189 entitled "SYSTEM AND METHOD FOR
DETERMINING SIMILARITIES BETWEEN ONLINE ENTITIES" filed Dec. 10,
2012, now U.S. patent Ser. No. ______, which claimed the benefit
the benefit under 35 U.S.C. .sctn.119(e) of U.S. Provisional
Application No. 61/570,606, entitled "SYSTEM AND METHOD FOR
IDENTIFYING COMMON INTERESTS BETWEEN AUTONOMOUS ENTITIES" filed
Dec. 14, 2011, the disclosures of which are incorporated herein by
reference.
FIELD OF THE INVENTION
[0002] The present invention relates generally to identifying and
quantifying similarities of interests between different Entities
across the various social networks, social applications, and online
communities that define The Social Web. More specifically, it
relates to exchanges that occur between a plurality of Users and
the ability to track and establish a valuation of similarity for
one or more elements such as Fields of interest.
BACKGROUND
[0003] The Internet is rapidly becoming a global community of
information exchange. This growth in connectivity, coinciding with
the evolution of hand held devices makes Internet connectivity and
socialization a growing part of our immediate, everyday lives.
Evolving Social Networks, search engines and the ability to share
personal opinion through community platforms are creating an
increasing social complexity and a glut of social data and
information that is challenging the effectiveness of the Internet's
open-source architecture. This requires certain systematic
standards that recognize the value of online Users and the
information they share in order to provide more meaningful
connections between people and information.
[0004] Within the context of a single Social Network--or any form
of online community platform--most people are familiar with the
natural and free flowing exchanges and discussions that tend to
develop. Whether the topic of discussion be that of endurance
sports, surfing, pets, gardening, cooking, survival tactics,
dating, wine & cheese, education, business, politics or just
about anything, there seems to be no shortage of people willing to
offer comment and suggestion.
[0005] Yet, across the multitude of online communities that define
the Social Web, there is no standard in place for validating and
valuing people and information resources (posts, discussions,
groups, communities, or other online entities such as music, video,
products, services, and so forth. In essence, online users are left
entirely to their own assessment for evaluating who is and is not a
valid contributor, community, post or discussion. While feedback
and rating systems provide various means for ranking or
recommending social media objects such as songs, videos, products,
restaurants, accommodations, and so forth, these raking systems are
open to bias feedback and fraudulent results. In addition, although
there is a vast amount of information provided by most Social
Networks, it is often very difficult for a person to discover
posts, discussions, communities, or even just other Users who
either share similar views or perhaps may be a credible and
valuable resource for learning something new.
[0006] More specifically, a comment about surfing locations, boards
or wax may well be offered by a life time surfer who truly knows
his or her stuff, or a land locked person who has never seen the
ocean and despises the surfing culture. The simple use of terms
related to Surfing by the primary author is not really sufficient
by itself to establish the author as an authority, and a simple
searching on those terms may or may not result in helpful
identification of that author as a good source for surfing
information.
[0007] As users become more reliant upon search engines to find
information, it is very desirable for the search engines to be more
accurate in identifying the meaning of search criteria. Likewise
there is a growing need for social networks to provide more
meaningful connections between people and information. The
challenge lies in understanding such an expression as "Hot Dog."
Does this mean the food, a canine with an elevated blood pressure
or an expression of amazement? Likewise the word "Jaguar" could be
a jungle cat, a luxury vehicle or the NFL sports team from
Jacksonville. Misunderstanding the context of association between
the terms may and often does, result in erroneous search
results.
[0008] In some cases, search engines permit a search wherein a
first term is used within X words or characters of a second term.
Though perhaps helpful for identifying specific documents or
articles, this methodology does not scale to groups of discussions,
articles, communities or other related entities and still may not
recognize the context as intended by the author. Moreover, such
search systems are constructed with the view that if terms exist
within proximity to each other they must be related--but this is
not always the case. In addition, such methodology is focused
strictly on the relationship of the terms with respect to each
specific document and cannot and does not permit a greater
awareness of the relationship of the terms in a greater
context.
[0009] Though perhaps an extreme example, the issues of identifying
similarities with other Users or Entities such as posts,
discussions, or other online communities may be quite important
when a parent is looking for safe birthday ideas for children,
advice on nut allergies or other issues where misguided responses
or even intentionally malicious responses could pose actual
harm.
[0010] Likewise, the issues of identifying similarities with Users
and social media objects (entities) that suit their interests, such
as songs, videos, products, services, etc., is essential providing
meaningful results when it comes to online search engines,
recommendations, advertising, skill matching, problem solving,
etc.
[0011] The frustrations with a single site are appreciated to
compound when looking at multiple sites. A User very qualified for
a particular subject, say marathons, may be entirely new to a site
and therefore even regular contributors may not recognize him or
her, let alone appreciate that there are interests in common Nor
will this User be able to find the Entities i.e. other Users,
posts, discussions, groups, other communities, or social media
objects that suit his or her varying degrees of interest.
[0012] Subsequently the ability to authentically recognize credible
and reliable sources that relate to specific subjects of interests
not only benefits the end User, but also communities, institutions,
governments and all forms of organizations by enhancing semantic
and social analytics, consumer trends, ad targeting, market and
product analysis, while providing a more viable source for ratings,
feedback and reviews.
[0013] In essence, the open-architecture of the Web requires a
better standard for providing the right information to the right
people at the right time. A system that generates authentic
credentials and establishing accurate similarities, as a means to
filtering information or controlling privacy, visibility, and
connectivity between people and information, would serve the best
interest of the people and organizations that use the Web. The lack
of an authentic social standard has resulted in misinformation,
intrusive/inaccurate advertising, threats to privacy, and malicious
behavior by unwanted, trolling individuals over open forums and
discussions.
[0014] Due to these concerns, the Web is still unsafe when it comes
to open exchange between people, their knowledge and information
resources. Therefore, private institutions such as enterprises,
schools, universities, governments, or other organizations, are
reluctant to embrace open social integration that would benefit
their cause (i.e. credentialing, research and development,
training, education, job placement, cross-platform communication,
community management, social integration, etc.)
[0015] What is necessary is a systematic standard for establishing
online credentials in order to recognize the similarities between
the various parts that define the Social Web, i.e. the keywords,
the people, their posts, the discussions, the communities, groups,
and including social media objects such as songs, videos, products,
services, etc., thus providing privacy and safety through better
organization between the different elements of the social Web.
[0016] Hence there is a need for a method and system of determining
similarities between Entities that is capable of overcoming one or
more of the above identified challenges.
SUMMARY
[0017] Our invention solves the problems of the prior art by
providing novel systems and methods for determining similarities
between online entities.
[0018] In particular, and by way of example only, according to one
embodiment of the present invention, provided is a method to
determine similarities on at least one Social Network including:
gathering metadata from at least one posting by a First User on a
first Social Network to define at least one First Field associated
with at least one First Entity, each associated First Field having
a value; evaluating responses to the posting by at least one Third
Party, and in response to the Third Party using one or more of the
First Fields, incrementing the value of each used First Field; and
providing an indication of the values of each First Field
associated with each First Entity, the indicated values permitting
a determination of similarity to at least one Second Entity
querying for at least two Fields.
[0019] In yet another embodiment, provided is a method to determine
similarities between online Entities on at least one Social Network
including for each entity: establishing a Database of Fields
collected from a First Discussion on a first Social Network, the
Discussion including a plurality of postings by at least one first
User and at least one second User, the Fields associated with at
least a First Entity; assigning a value to each Field based on
frequency of use of each Field within the First Discussion; and
evaluating the values of each Field to one another to establish a
first table providing a context of association between Fields to
identify the First Entity has having a quantified level of
interests as identified by each Field, the values permitting a
determination of similarity to at least one Second Entity querying
for at least two Fields.
[0020] Still, in yet another embodiment, provided is a system for
determining similarities between Entities including: a Metadata
Gatherer structured and arranged to gather metadata from at least
one first Social Network regarding at least one User identity, the
gathered metadata including at least one Field obtained from at
least one posting by the at least one User identity and subsequent
third party responses to the at least one User identity; a Database
structured and arranged to associate the at least one Field to at
least one Entity; and a value determiner structured and arranged to
determine a cumulative value for each Field associated to each at
least one Entity, the value for each Field determined by assigning
a value to at least a portion of the metadata of each third party
response and aggregating the assigned values for each Field,
evaluating the aggregate values of each Field to one another to
establish a first table providing a context of association between
Fields to identify the First Entity has having a quantified level
of interests as identified by each Field, the aggregate values
permitting a determination of similarity to at least one Second
Entity.
[0021] And in yet another embodiment, provided is a non-transitory
machine readable medium on which is stored a computer program for
determining similarities between online Entities on at least one
Social Network the computer program comprising instructions which
when executed by a computer system having at least one processor
performs the steps of: gathering metadata from at least one posting
by a First User on a first Social Network to define at least one
associated First Field provide by the at least one First User and
occurring in the at least one posting, each associated First Field
having an initial value; evaluating responses to the posting by at
least one Third Party, and in response to the Third Party using one
or more of the associated First Fields in the response,
incrementing the value of each used associated First Field; and
providing an indication of the values of each associated First
Field associated with each First Entity, the indicated values
permitting a determination of similarity to at least one Second
Entity.
[0022] Further, according to one embodiment of the present
invention, provided is a method to determine similarities on at
least one Social Network including: gathering metadata from at
least one posting by a First User on a first Social Network to
define at least one First Field associated with at least one First
Entity, each associated First Field having a value; gathering
metadata from at least one Third Party response to the posting by
the First User to define at least one Second Field associated with
at least one Second Entity, each associated Second Field having a
value; evaluating the metadata of the at least one Third Party
response related to the posting by the First User to increment the
value of the at least one First Field as associated with each First
Entity; and providing an indication of the value of each First
Field and Second Field associated with each First Entity and Second
Entity to indicate a value of similarity between each First Entity
and Second Entity.
BRIEF DESCRIPTION OF THE DRAWINGS
[0023] At least one method and system for determining similarity
between online Entities of at least one site will be described, by
way of example in the detailed description below with particular
reference to the accompanying drawings in which like numerals refer
to like elements, and:
[0024] FIG. 1 illustrates a high level conceptual view of the
Similarity Determining System in accordance with at least one
embodiment;
[0025] FIG. 2 is a flow diagram illustrating a method of similarity
detection in accordance with at least one embodiment;
[0026] FIG. 3 illustrates exemplary Database entries for known User
Identities in accordance with at least one embodiment;
[0027] FIG. 4 is a conceptual illustration of a Discussion on a
first Social Network involving multiple Entities participating in
similarity determination in accordance with at least one
embodiment;
[0028] FIG. 5 illustrates exemplary Database entries for at least a
group of Entities involved in the Discussion shown in FIG. 4 in
accordance with at least one embodiment;
[0029] FIG. 6 is a conceptual illustration of a second Discussion
on a Social Network involving multiple Entities participating in
similarity determination in accordance with at least one
embodiment;
[0030] FIG. 7 illustrates exemplary Database entries for at least a
group of Entities involved in the Discussion shown in FIG. 6 in
accordance with at least one embodiment;
[0031] FIG. 8 illustrates the combination of tables for User
Entities in accordance with at least one embodiment;
[0032] FIG. 9 illustrates the comparison of tables for different
Entities associated with different Discussion in accordance with at
least one embodiment;
[0033] FIG. 10 is a conceptual illustration of a Discussion on a
first Social Network involving multiple Entities such as individual
Users providing comments regarding a social media object Entity
such as a resort to further illustrate that a higher order Entity
may also develop field value for similarity determination in
accordance with at least one embodiment; and
[0034] FIG. 11 is a block diagram of a computer system in
accordance with certain embodiments of the present invention.
DETAILED DESCRIPTION
[0035] Before proceeding with the detailed description, it is to be
appreciated that the present teaching is by way of example only,
not by limitation. The concepts herein are not limited to use or
application with a specific system or method for determining
similarity between Entities. Thus although the instrumentalities
described herein are for the convenience of explanation shown and
described with respect to exemplary embodiments, it will be
understood and appreciated that the principles herein may be
applied equally in other types of systems and methods involving the
determining similarity between online Entities.
[0036] To further assist in the following description, the
following defined terms are provided.
[0037] "Social Network" as used herein is also understood and
appreciated to be any online community platform where Users are
identified by some form of User ID and make some level of exchange
between themselves through Entry/Response. In other words a Social
Network is appreciated to be any Internet based system that
provides any form of media (i.e., posts, blogs, articles, products,
services, pictures, audio commentary, music, pictures video,
responsive email, chat, etc. . . . ) that can be responded to by
identified Users of that system. Moreover, in some embodiments the
Social Network may be described as an online community platform. At
times these online community platforms can contain sub communities
within a parent community, such as in news media where a parent
community might have different sections such as sports, politics,
business, etc., or in an education setting where an online
University may have different departments, courses, etc.
[0038] "Entity"--An Entity is recognized and defined by any social
media object that can be associated with Fields and their Values
that are generated through Users Entry/Responses in online
Discussions. Typically, and reviewing from the bottom up, Social
Network Users provide Entries/Responses that form Discussions and
Discussions occur within Communities and at times Communities can
have Parent Communities. Each User, Entry/Response, Discussion,
Groups, Community and Social Network itself may be viewed as an
Entity, with each higher order entity (e.g., the Discussion),
comprising lower order Entities (e.g., the Entries/Responses by
Users). Likewise, community Entities can be the children of parent
communities as is the case for an online classroom that is part of
a department of a university. The Fields and Field Value of each
higher order Entity is the result of the aggregation of all of its
lower order Entities. For example: the Discussion's Field's and
Field Values are the result of all Field and Field Values that
arise from each User's Entry/Response within that discussion.
Determination of Similarity is made on an Entity to Entity basis
where each Entity may be a high order or low order entity. There
are other forms of Entities, such as an Interest Group, which is
further defined below. It should also be noted that a social media
object, such as an article, a photo, a song, a video, an image, a
game, an advertisement, a product, a service, etc., can be
considered Entities if they are directly related to any form of
online Discussion, in this regard the system treats each of these
objects as the Discussion itself. Also, through the Similarity
Determining System, similarities between Entities can be defined as
a "follower" "connection" or a "friend" with one another.
[0039] "User"--He or she who is providing the data in an
Entry/Response. Users are also considered Entities based on the
Field and Field Values they receive through online Discussion. A
user can be an actual living person using the Web, or a machine
generated user, as is the case in Artificial Intelligence.
[0040] "Community"--An Entity that relates to a forum or group of
Discussions having at least one commonality. This commonality can
be something as simple as the desire to share information over the
Web, as with massive sized social networks. Communities can also be
hierarchical and share something more specific. Such as the class
"Introduction to Physics" is a community that is itself a
sub-community of the University providing the class. Likewise a
section of a Social Network site dedicated to Science is a
Community that is itself a sub-community from the overall Social
Network, and a sub-community such as Astronomy or Physics may each
be a sub-community of the Science Community. A community can be as
small as two people having a discussion via email, to hundreds of
millions of people having discussions over a very large social
network. The entire Internet itself can be considered a macro
community of all the online communities it is comprised of, which
can also be considered as "The Social Web."
[0041] "Entry"/"Response"--An Entity that is defined by the data
provided by a User in a posting or in response to a posting on an
Internet based Social Network site, and/or community platform. For
example, but not limited to, a post, article, tweet, like, dislike,
rating, product, picture, comment, email, instant message, or other
indication or expression of an opinion of any separable entity
involved in the Web. Moreover, the data may be textual--as in a
written comment, non-textual--as in a "Like" or a "Thumbs Up", or a
combination of textual and non-textual elements such as a textual
Response that includes a rating scale. Since each Entry/Response
may insight a tangent discussion, each Entry/Response can also be
considered its own Discussion.
[0042] "Non-textual Entry/Response"--A Posting that has limited or
no text, such might be the case for a social media object such as
an image, song, video, an advertisement for a product or service,
or a sign or symbol that relates to a rating such as a thumbs
up/thumbs down, a 5 star scale, a like, a dislike, etc. In such a
case the system can default to the associated Fields of any parent
Entity of the Entry/Response as the means for recognizing
associations and valuing Fields from other Entities.
[0043] "Entry/Response Hierarchy"--The Entry/Response Hierarchy is
defined through Entries and subsequent Responses that create
threaded, or nested, Discussions that relate to specific topics of
interest. Every time a new original Entry/Response is made, a new
Hierarchy can be created and this begins a new Discussion. Since
each Entry/Response may insight a tangent discussion, each
Entry/Response can also be considered its own Discussion. Every
time an Entry/Response is made in relation to an existing
Hierarchy, the Hierarchy is adjusted for that Entry/Response. The
Entry/Response Hierarchy is used to define the levels of engagement
in order to determine appropriate Field Value for branching out
discussions.
[0044] "Discussion"--Discussions are Entities started by and
defined from Entries and Responses to those Entries. Through
subsequent Response to an Entry the Entry/Response Hierarchy is
generated based upon specific topics of interest and this results
in a Discussion. Since each Entry/Response may insight a tangent
discussion, each Entry/Response can also be considered its own
Discussion. Discussions are subjects that draw others Users to
respond to the data posted by Users, and are defined by an initial
entry, article, post, blog, tweet, product, email, instant message
or anything that can be responded to, rated, or commented on, that
would start a threaded Discussion. Discussions can also relate to
social media objects such as songs, pictures, videos, products,
articles, etc. in order for the system to recognize these objects
as their own Entities.
[0045] "Metadata"--This is data about data and relates to tags, key
words, or key terms, that are extracted and recognized within this
system and method as Fields. Metadata can comprise one or more
Fields. Metadata can be derived through blogs, postings, articles,
songs, pictures, voice recognition, tags, etc. Indeed, the metadata
may be the data itself as directly provided by a User in an
Entry/Response, an indicator such as a rating (like or dislike,
thumbs up or thumbs down, etc. . . . ), and data associated with
any form of an Entry/Response, such as but not limited to, the site
IP, date, time, author, last editor, etc. . . . .
[0046] "Field(s)"--Are relational entities such as Metadata, tags,
key words, phrases, strings of text, or key terms as are commonly
understood in searching and organizing data. Fields are defined
from an Entry/Response through information generated from the
information provided by the source of Entry and all Responses to
that Entry. Fields can be generated by the 3rd-party Social
Network, Users or the Similarity Determining System itself. These
may be one or more terms. Fields create universal Metadata that are
specific to the Similarity Determining System and can be utilized
across a plurality of Social Networks in order to recognize
similarity between Entities. A Field can also be recognized as an
Entity--as a Field builds associations to other Fields through
their shared associations to other Entities. When matching Fields
between Entities, the system can also determine similarities
between non-identical Fields, therefore, a Field can be a
pseudonym, abbreviation, or slang and still match a similar Field.
For example: a term such as "Fished", could be associated with
"Fishing," or "Fins" could be associated with "Dolphins," or "MJD"
could be associated with a famous football player named "Mourice
Jones-Drew," etc. Although a Field may incorporate metadata, it is
understood and appreciated that as used herein, a Associated Field
is an element that is clearly and obviously a component of the
discussion and/or posting--it is a Social Media element that is
clearly provided by one Entity so as to share a thought, idea,
opinion, etc. . . . with others. it is a textual element or phrase
provided by a User, it is an image, graphic or audio element
provided by a User as an intentional element of the discussion or
posting. Moreover, a Field associated with a Entity is a user
perceived element--something recognized and understood by another
person as an intended component of the discussion. It is not simply
a latent element that may be communicated as part of the data
exchange in the posting processes, i.e. an IP address, date, time,
MAC address, browser type, etc. . . . . A Field is an element
intentionally provided by person as a human perceptible element of
communication--a word, phrase, image or sound.
[0047] "Field Value"--Is the value applied to a Field. Moreover, a
Field in a new original Entry, or a new Field to an existing
discussion has no Field Value, or a Field Value of 1. As discussed
below, for at least one embodiment Field Value is based on the
frequency of Responses overall, where the Response is located in
the Entry/Response Hierarchy, the Ratings from those Responses, as
well as the frequency of Field usage in subsequent Responses.
Moreover, Field Value develops through subsequent use of a Field by
Third Parties through the non-subjective, automatic assignment of
additional value--i.e., direct response using Field adds value of
"1" to Field Value and indirect response using Field adds a value
of "0.5" to the Field Value. This automated assignment of
additional value results in the development of aggregate Field
Value. For at least one embodiment, if a Field is not used for a
period of time, there may be an automatic decay applied as well to
the aggregate field value such that the aggregate field value may
dissipate over time. The overall Field Value applied to a User or
Entity in Association to a Field is the aggregate of all Field
Values defined through Discussions that relate to that Entity.
[0048] "Interest Group"--A grouping of two or more Fields and their
values which can be defined by the Similarity Determining System or
an Entity such as a User or a Community. Since Interest Groups are
comprised of Fields and Values they are also considered an Entity.
Interest Groups provide more accurate similarities based on the
number of Fields it provides for matching similarities between
Entities. For example: a User could create an Interest Group called
"Surfing California" and include the Fields "Surfing,"
"California," "Beaches" and this would create more accurate
similarities between Entities that share these same levels of
interest. Likewise, Interest Groups can assist by providing greater
accuracy in determining similarities between entities. They can
also be used for visibility and privacy settings between
entities.
[0049] To briefly summarize, provided is a system and method for
determining similarities between online Entities on at least one
Social Network. This determination of similarities is in essence
based upon 3.sup.th party Responses and/or exchanges occurring over
at least one Social Network, and not a User's, group's, or
community's own statements of self worth or other peoples opinion
of value. Moreover, it is a system and method that involves
gathering metadata from at least one Discussion involving at least
one User identity on a first Social Network. This Metadata is used
to define at least one First Field associated with at least one
First Entity. The Metadata of at least one third party Response
relating to the posting is then evaluated and in Response to the
Third Party using one or more First Fields, the value of each used
First Field is incremented. An indication, such as a total value,
of each First Field associated with the First Entity is then
provided, the indicated values permitting a determination of
similarity to at least one Second Entity querying for
similarity.
[0050] In other words, the degree of similarity is understood to be
determined both by the appearance of common Fields between two
Entities, but also how the Fields relate to one another within
their association to each Entity. More specifically, an Entity such
as a User, a Post, a Discussion, a Group, or a Community having the
Fields "Beach" "California" and "Surfing" is more similar to
another Entity having these same Fields of similar value. Yet
another Entity having only the Fields "Beach" and "Surfing" of
dissimilar values may indicate that these Fields are not used in
the same context or frequency. Indeed the Similarity Determining
System 100 does not merely query for common terms among Entities,
but assists Users in further understanding the possible degrees of
similarity by also providing an indication for how those terms are
used in relation to each other, by or in context with the
Entity.
[0051] Likewise, while it is the goal of the system to create
advantageous relationships between Entities by querying for at
least two Fields as a matter of determining more accurate context
of association, indeed there are occurrences when an individual
Field may be substantial, on its own, to define a specific context.
Such is the case for an event such as "The 2013 NBA Finals" or a
favorite restaurant "Jack's Crab Shack" or a favorite sports star
"Maurice Jones-Drew" or even a summary of words combined into a
single sentence that the System recognizes as an individual Field
such as a headline or summary of a blog, post or an article.
[0052] Moreover, for at least one embodiment, the Similarity
Determining System has the ability to receive information and more
specifically, information that defines Fields through metadata,
tags and key words, including information that defines ratings. In
at least one embodiment this information also includes the
designation of a Discussion, as an Entity, which as stated in the
definitions above is initiated from the initial Entry/Response, or
subsequent Entry/Response, that would start and build the
Entry/Response Hierarchy. Indeed a Discussion may arise from an
initial posting, or a new Discussion may emerge from a subsequent
Entry/Response where a new topic of interest for Discussion is
introduced.
[0053] By implication, as the Users Post may be an Entity of low
order, and a Community to which the User belongs may be an Entity
of higher order to the Users Post, the association of the Fields to
the User Post may also be attributed to higher order Entities to
which the User Post is related, for example--the User, the
Discussion, the Community, and the Social Network are all higher
order Entities that relate to the Users Post.
[0054] FIG. 1 is a high-level block diagram of an embodiment of the
Similarity Determining System 100. As shown the Similarity
Determining System is in communication with a first Social Network
102, and at least one or more Users, of which Users 104, 106, 108
and 110 are exemplary. In at least one embodiment, the Similarity
Determining System 100 is a component of the first Social Network
102
[0055] The first Social Network 102 and the Similarity Determining
System 100 are understood and appreciated to be one or more
computer systems, (including microprocessors, memory, and the like)
adapted at least in part to provide the first Social Network 102
and the Similarity Determining System 100. More specifically each
may be a general computer system adapted to operate as a Social
Network, such as first Social Network 102 and/or the Similarity
Determining System 100, or a specialized system that is otherwise
controlled by or integrated with a computer system.
[0056] For such embodiments, Users 104, 106, 108 and 110 may be
identified as known or registered Users on the basis of having
established accounts with the first Social Network 102. In such
embodiments, the Users of the first Social Network and more
specifically the Similarity Determining System 100, may not need to
provide additional information to the Similarity Determining System
100 to permit monitoring and determination of similarity to occur
as their respective associated User Id. Entities are already known
as are the parameters of the first Social Network 102.
[0057] In varying embodiments, Users 104, 106, 108 and 110 may
become known or registered Users by establishing User' Accounts 118
directly with the Similarity Determining System 100. For
embodiments wherein the Similarity Determining System 100 is in
communication with a plurality of Social Networks, e.g., first
Social Network 102 and one or more second Social Networks 112, 114,
116, additional access information for all of Social Networks may
be provided by the User in his or her User Account 118.
[0058] In addition, each User Account 118 may define one or more
User IdEntities that are associated with the known User in various
different Social Networks. Moreover, for at least one embodiment,
the User Accounts 118 define for the Similarity Determining System
100 the User Identities to be monitored, evaluated, authenticated
and reviewed for similarity with other Entities upon one or across
many Social Networks.
[0059] In at least one alternative embodiment, the Similarity
Determining System 100 is distinct from the Social Network 102.
Further, whether a component of the first Social Network or
distinct from the first Social Network, in varying embodiments the
Similarity Determining System 100 is also in communication with a
plurality of second Social Networks, of which second Social
Networks 112, 114 and 116 are exemplary.
[0060] To facilitate this, in at least one embodiment, the
Similarity Determining System 100 has a Metadata Gatherer 120, an
Association Scheme 122, a Value Determiner 124 and a Database 126.
For at least one embodiment, the Similarity Determining System 100
is a an adaptation of U.S. patent application Ser. No. 13/239,100
filed Sep. 21, 2011 and entitled "System and Method for
Authenticating a User through Community Discussion" now U.S. Pat.
No. 8,806,598 and incorporated herein by reference. More
specifically, application Ser. No. 13/239,100 teaches at least one
system and method for assigning value to Fields occurring in an
online community discussion--these values being used by the present
invention for determining similarity between other Entities. For
such an adaptation, the Value Determiner 124 is substantially the
authenticator as set forth and described in application Ser. No.
13/239,100. For the sake of this application this valuation and
authentication process is extend to other Entities, not just to
Users, but to their posts (i.e. Entry/Response), the Discussions,
the Communities, the Social Network and other Entities that relate
to the source of authentication described in application Ser. No.
13/239,100.
[0061] As is further discussed below, the Database 126 is
structured and arranged to track and associate use of Fields to
Entities, such as but not limited to the Social Network, the
Community, the Discussion, the Group, the Posts (i.e.
Entry/Response), each User engaged in the Discussion, as well as
the Fields themselves. Moreover for each potential Entity as
defined for an instance of the Similarity Determining System 100,
the Database 126 provides collections of Fields, such as the
Community Collection 128, Discussion Collection 130, User
Collection 132, Entry/Response Collections 134, and/or other Entity
collections, not shown. Of course, within each collection there may
be sub-collections, such as the Discussion Collection 130 having
internal collections for each Entry/Response.
[0062] The Metadata Gatherer 120 in connection with the information
provided in the User Accounts 118 monitors community activity
within at least the first Social Network 102. When any User
established with the Similarity Determining System 100 makes an
Entry or Response, the Similarity Determining System 100 gathers,
via the Metadata Gatherer 120, appropriate data from the Entry or
Response and the subsequent Responses. This includes attributes
such as date and time, User name, message content, message title,
tags, key words, ratings information, etc. . . . . Moreover, the
data from the Entry or Response may be any data associated with the
Entry or Response--that which is provided directly as the textual
or non-textual Entry or Response or that which is supplementary to
the Entry or Response.
[0063] In at least one embodiment, the gathered metadata will
include at least one Field obtained from at least one posting by a
known User identity and subsequent third party Responses to the
known User identity. The Database 126 is structured and arranged to
record the association of at least one Field to the known User
identity. For embodiments where the User account 118 are not
specifically maintained by the first Social Network 102, the
Database may further be structured and arranged to maintain the
User Accounts 118 as well.
[0064] As is further explained below, for at least one embodiment,
if the Similarity Determining System 100 determines that the User
posting the Entry/Response is not a known or registered User, the
Similarity Determining System 100 may invite the User to become a
registered User and therefore also enjoy the benefit of the system.
For yet other embodiments, the User posting the Entry/Response need
not be a known or registered User for the value of one or more
Fields to be increased and the determination of similarity thereby
improved.
[0065] Metadata, tags, key words, and key terms generated from the
Entry/Responses as text become Fields and permit the Similarity
Determining System 100 to establish relationships between other
Entities through associations to Fields derived from the
Entry/Responses within the Discussion. Data generated from
non-registered Users enters the Entry/Response Hierarchy in order
to maintain the flow of Discussion in relation to topic of
interest. However, in at least one embodiment as the User is not a
registered User, the entry of the data does not create associations
or Field Values related to the unregistered User.
[0066] In another instance if an unregistered User can be
identified through a unique identifier such as an email address,
password, or unique User name, then the non-registered,
identifiable Users, their associated Fields, and the values of
these Fields, can be determined and sent to a temporary Database
location. If this User decides to become a registered User of the
system, these Fields and there values can be immediately updated to
their profile after proof that they are that actual User.
[0067] The Association Scheme 122 recognizes the Associations
between an Entity, such as for example the registered Users, and
defined Field(s). The Similarity Determining System 100 builds an
aggregate of associations based upon frequency and usage of
specific Fields per Entry/Responses by each User. As the Fields are
tracked with respect to the developing Entry/Response Hierarchy the
Users who engage in the Discussion, their Entry/Response, the
Discussion itself, and the Community in which the Discussion is
occurring, each of these Entitles may be ascribed an associated
value for each Field.
[0068] These Fields and their associated Field Values are indicated
to Users and other Entities of the Similarity Determining System
100, and in at least one example this is achieved with a popup or
hovering window that provides at least a partial listing of the
Fields and their associated values. As the values are also
evaluated against one another, they provide a context of
association between the Fields so as to identify the First Entity
as having a quantified level of association as identified by the
value of each Field. Moreover, the context of association for at
least one embodiment is determined by comparing the values of each
Field and ranking them--such as in ascending or descending order. A
first Field having a value of 70% or greater of a second Field is
evaluated to have a stronger context of association as compared to
a first Field having a value of 30% or lesser of a second
Field.
[0069] Of course it will be appreciated that higher order Entities
may see an aggregation of identical Fields--for example a first
User's Entry/Response may have an associated Field "Marathons" with
a developed point value and a second User's Entry/Response may also
have an associated Field "Marathons" with a developed point value.
As both the first User's Entry/Response and the Second User's
Entry/Response are part of the same Discussion, called "Disney
Marathons" the Discussion Entity "Disney Marathons" receives value
for the Field "Marathons" from both the first and second User's
Entry/Response. The aggregation of value is specific to Users
Entry/Response, which aggregate into the value for the Discussion,
the Community, and any parent Communities that may exist.
[0070] It should also be appreciated that matching Fields between
Entities can also occur through matching non-identical Fields--for
example, when matching Fields between Entities, the system can also
determine similarities between non-identical Fields that are indeed
similar. In this regard, a Field can be a pseudonym, abbreviation,
or slang of a matching Field. For example: a term such as "Fished"
could be associated with "Fishing," or "Fins" could be associated
with "Dolfins," or "MJD" could be associated with a famous football
player named "Mourice Jones-Drew." In this case, if the system can
determine a similarity between non-identical Fields. Therefore,
when associating Fields and incrementing Value between posts,
non-identical Fields can result in an associated of either of the
non-identical Fields.
[0071] Where the Similarity Determining System 100 is in
communication with a plurality of Social Networks, this reference
of association permitting a determination of similarity is viable
across the plurality of Social Networks with respect to different
Entities. In varying embodiments, the Metadata Gatherer 120 and/or
the Association Scheme 122, alone or in varying degrees of
combination may establish the Entry/Response Hierarchy 136 as a
substantially distinct component of the general Database 126.
[0072] The Value Determiner 124 determines Field Values for each
Entry/Response. For at least one embodiment this determined Field
Value is also based on depth of subsequent User Entry/Response.
This Field Value is triggered by each subsequent Entry/Response,
and is adjusted by order in the Entry/Response Hierarchy, and/or
Ratings Adjustment, and Field Average as is defined by the prior
art in U.S. patent application Ser. No. 13/239,100 now U.S. Pat.
No. 8,806,598. For at least one alternative embodiment, Field Value
is determined by frequency of use for each Field, such as for
example tag clouding.
[0073] Further, for at least one embodiment, the Value Determiner
124 is also structured and arranged to detect non-textual
responses, such as but not limited to a "Like," "Thumbs Up,"
"Smiley," or star rating which are also evaluated and used to
adjust Field Values. Moreover, as the Field Value is determined by
subsequent responses, whether textual or non-textual, a variety of
different methodologies for determining Field Value may also be
adapted and employed.
[0074] In one method, if a Field cannot be determined through the
Metadata from a non-textual Entry/Response, then the system can
identify associated Fields from the higher level Entities of the
non-textual response, such as the User who posted the non-textual
Entry/Response, or from other related Entities such as the
Discussion, or the Community the non-textual Entry/Response belongs
to. For example, if a User "thumbs up" an article on surfing, even
though the response "thumbs up" did not include the Field
"Surfing," if the User Entity has an association to the Field
"Surfing" then an association can be made between the two Entities.
Likewise, if every response is a non-textual response, the system
can evaluate Fields associated with parent Entities, i.e. the
Users, the Group, the Community, etc., can be associated to the
Entities that relate to that Post.
[0075] As is the case for matching Entities (through querying) that
do not include any Fields, such as a Post without a response, the
system can utilize the Fields of other related Entities, such as
the User, the Discussion or the Community, in which the Post
belongs to, in order to recognize association and establish
valuation. This is the case only as long as the higher-level Entity
has already established an association to one or more Fields and a
Value for those Fields.
[0076] With respect to FIG. 1, it is understood and appreciated
that the elements, e.g., Metadata Gatherer 120, the Association
Scheme 122, the Value Determiner 124 and the Database 126 are in
one embodiment located within a single device, such as for example
a computer. In at least one alternative embodiment, these elements
may be distributed over a plurality of interconnected devices.
Further, although each of these elements has been shown
conceptually as an element, it is understood and appreciated that
in varying embodiments, each element may be further subdivided
and/or integrated within one or more elements.
[0077] FIGS. 2-9 provide a high level flow diagram with conceptual
illustrations for a Discussion upon an exemplary Social Network
site, e.g., first Social Network 102, and subsequently at least one
additional Social Network site, e.g., second Social Network 112. It
will be appreciated that the described events and method need not
be performed in the order in which it is herein described, but that
this description is merely exemplary of one method of implementing
a method to achieve the Similarity Determining System 100, or more
specifically a method of determining similarity between Entities
upon one or a plurality of Social Networks.
[0078] In addition, for ease of illustration and Discussion the use
of textual Discussions have been shown, however it is to be
understood and appreciated that other options for media, such as
but not limited to one or more pictures, movies, audio files,
songs, or even links to other media may be used at least as part of
the initial posting. Often, with such media, there is also a
clearly identified subject--such as a caption or title. When this
exists, the subject is recognized by the Similarity Determining
System 100 and method 200 as the original Entry/Response and
therefore regarded as a Discussion.
[0079] Of course, it is further understood and appreciated that
where the posted media is non-textual, metadata may still be
collected, such as but not limited to the type of media, time of
posting, the User Entity as the source of posting, the Discussion,
or the Community itself. For at least one embodiment, a non-textual
positive response, such as a "Like," "Thumbs Up," "Smiley," or star
rating is recognized and evaluated for at least a partial
incremental increase of the point values for the Fields in the
posting to which such a non-textual response is offered.
[0080] Moreover, if the nature of the Discussion is such that a
title is clearly provided, the Similarity Determining System 100
and method 200 accept that as the title of the Discussion. Of
course for the determination of similarity, a title is not
specifically required, though certainly it may be helpful. If the
nature of the Discussion is such that a title is not clearly
provided, the Similarity Determining System 100 and method 200 may
simply focus on the associated Fields defined within the first
level Entry/Response or through recognizing a string of initial
characters of that Discussion as its title.
[0081] It is also understood and appreciated that the methodology
of determining similarity may take many forms. The total number of
Responses to an initial posting may be simply tallied, direct
Responses may be valued differently from credible Responses,
heuristics may be applied to gage a Response as being positive or
negative or neutral, (note: a key component of this system is that
it does not need, or use, objective User information such as age,
sex, etc. . . . ). Different methodologies for valuation may also
be established for different embodiments of Similarity Determining
System 100. With respect to the Discussion herein, it is understood
and appreciated that the description of determining similarity is
merely exemplary of one method of operation in accordance with the
present invention, and not a limitation.
[0082] With respect to FIG. 2, in addition to illustrating the
steps of the method 200, there is an attempt to further illustrate,
in general, which elements of Similarity Determining System 100 are
in play at different stages. Accordingly along the left side of the
flow diagram is presented a conceptualization of a Database, such
as Database 126, and the correlated elements within the
Database.
[0083] The Similarity Determining System 100 is, as noted above for
at least one embodiment, implemented to provide a determination of
similarity across a plurality of Social Networks. It is understood
and appreciated that even where multiple Social Networks are
involved, determination of similarity can and does occur on
individual Social Networks.
[0084] As such, in the following description the methodology for
determination of similarity is presented with respect to one Social
Network, e.g., first Social Network 102, before demonstrating how
the determination of similarity may be expanded across multiple
Social Networks.
[0085] Although for at least one embodiment a base value of perhaps
"1" may be initially set for each Field, the subsequent repeated
use by the same User does not by itself generate significant
additional value. Rather, it is the responses by other Users, i.e.,
third parties, that generate Field Value, and thus establish
credibility for the original User with respect to each Field
subsequently used.
[0086] With respect to the issue of determining similarity, this
value generation based on third parties again further establishes a
degree of confidence that the User is indeed a credible source. In
addition as the Field Values are relevant to other Entities to
which the User is related, i.e., Entry/Response, Discussion,
Community and Social Network itself--the third party valuation
scheme further establishes credibility for Similarity when seeking
matches with any other Entity as well.
[0087] As shown in FIG. 2, the method 200 commences with
affiliating with at least one Social Network, block 202. For an
embodiment where the Similarity Determining System 100 is
implemented directly as a component of a Social Network, such as
first Social Network 102, the Users of the first Social Network may
all be identified as known or registered Users with no further
action 204.
[0088] For at least one alternative embodiment, whether integrated
as a component of the Social Network or not, a User sets up his or
her account and provides at least his or her associated User
identity and such other relevant information regarding the Social
Networks he or she uses, block 204.
[0089] With respect to the Database 126, FIG. 2 illustrates that,
for varying embodiments, the Database 126 receives and records the
basic information, such as affiliated Social Network(s) (records of
affiliated Social Network(s) 250), a listing of registered or known
Users (records of registered Users 252), and a listing of each
User's Social Network(s) (records of Social Networks affiliated
with Users 254). These records may certainly be combined, but have
been shown distinctly for ease of discussion.
[0090] FIG. 3 illustrates conceptual Database records.
Specifically, table of records 300 correlate to the listing of
registered Users (records of registered Users 252) and illustrate
the User Accounts. A first registered User 302 is shown as Spiff
Jones and a second registered User 304 is shown as Dan Mann.
Additional registered Users are not shown for ease of
illustration.
[0091] Table of records 306 conceptually correlate to the listing
of the first registered User's Social Networks (records of
registered Users 252) and specifically illustrate the Social
Networks with which User Spiff is associated. As shown, for each
Social Network, the registered User, e.g. Spiff, may use a
different username 308. Moreover, as each registered User builds
his or her history of associated Fields, these associations may
transcend across all associated Social Networks regardless of
username to permit determinations of similarity across
platforms.
[0092] Table of records 310 conceptually correlate to the listing
of the first registered User's Social Networks (records of
registered Users 252) and specifically illustrate the Social
Networks with which User Dan_Man is associated. As shown, for each
Social Network, the registered User, e.g. Dan_Man, may use a
different Username 312. Moreover, as each registered User builds
his or her history of associated Fields, these associations may
transcend across all associated Social Networks regardless of
Username to permit determinations of similarity across
platforms
[0093] Returning to FIG. 2, the Similarity Determining System 100
then commences to monitor the specified Social Network or networks
awaiting action by a registered User, block 206. For at least one
embodiment, there may be Users who are not registered Users of the
Similarity Determining System 100, decision 208. For at least one
embodiment, if the initial activity is by an unregistered User
these initial postings by such unregistered Users are ignored, and
the Similarity Determining System 100 remains in a monitoring
state, block 206.
[0094] For at least one optional embodiment, postings by
un-registered Users are trapped to initiate an offering for these
Users to become registered Users, decision 210. This may be
accomplished by initiating a new pop-up, application or appliance
that informs the User of the presence of the Similarity Determining
System 100, its function, features and benefits and how
determination of similarity achieved. His or her Entry/Response may
also be cached, block 212 during this account set up process so
that upon enrolling in the Similarity Determining System 100 he or
she is given immediate credit for his or her Entry/Response.
[0095] If the un-registered User accepts the offer to become a
registered User, he or she is then directed to the process of
setting up his or her account, block 204. Of course, if he or she
opts not to accept the offer to become registered, the method
continues and the un-registered User is simply treated as an
un-registered User.
[0096] In certain embodiments, Responses by un-registered Users can
be used in building Field Value, the values subsequently used in
the determination of similarities, if such a Response is related to
a prior posting by a registered User, decision 214. Where the
posting is indeed a Response, metadata may be gathered, block 216,
else the Similarity Determining System 100 remains in a monitoring
state, block 206. For at least one embodiment, values generated by
the evaluation of this metadata may be discounted as indicated by
optional block 218. Moreover, for at least one embodiment, all
third party Responses are evaluated in determining values to be
used for similarity analysis regardless of whether the third party
is a registered or unregistered User.
[0097] The Similarity Determining System 100 and method 200 are
adapted in at least one embodiment to act and determine Field Value
upon the occurrence of non-textual Responses--such as "Likes"
thumbs Up, Stars, or other non-textual expressions of approval or
disproval. However for ease of illustration and discussion, textual
Response are first considered.
[0098] When a registered User does initiate an Entry/Response, the
Similarity Determining System 100 recognizes that Entry/Response,
decision 208, and moves to the determination of whether it is a
Response, decision 220. For this new posting, Similarity
Determining System 100 gathers data from the posting to define at
least one first Field associated with at least one Entity, each
associated Field is also initialized with a value, block 222.
[0099] Where Similarity Determining System 100 determines the
posting to be a Response, decision 220, the Similarity Determining
System 100 moves to gathering metadata from the response, and more
specifically evaluating the response to the posting by the third
party, block 216. In response to the third party using one or more
of the first Fields, the Field Value of each used first Field is
incremented.
[0100] As indicated by the dotted lines, these Field Values are
associated with at least one Entity, such as for example the User
who provided the first posting. However, these Field Values may
also be associated with other Entities, such as Community 256, the
Discussion 258, the User 260, as well as Entry/Response 262--indeed
other Entities (Other 264) may also be defined, such as but not
limited to the entry/response sub-communities, parent-communities,
the Discussion itself, and the Social Network.
[0101] As the Field Values are adjusted based on the frequency of
use within the discussion, and/or the number of responses to an
Entry, and/or through subsequent response of each Field, the
Similarity Determining System 100 provides an indication of the
value for each associated Entity, block 224. Although the
Similarity Determining System 100 may display the values for all
associated Fields, more typically the Similarity Determining System
100 will display the values of the top Fields, or if responding to
a query for similarity the top matching Fields. It should also be
appreciated that this indication of values also provides an
indication of correlation as between the Fields. For example,
higher valued Fields are generally used more commonly with other
higher valued Fields then with lower valued Fields.
[0102] This indication of value permits a determination of
similarity to at least one Second Entity querying for at least two
Fields. As the Similarity Determining System 100 is aware of Users
and defined Entities, the display of Similarity to one or more
other Entities can be substantially real time. A User of the
Similarity Determining System 100 may also select to query for a
determination of Similarity with a specific Entity or type of
Entity--i.e., other Users, Posts Discussions, Communities, Fields,
Interest Groups, etc.
[0103] A User of the Similarity Determining System 100 may also
specify a desire to check for similarity, decision 226. In such an
instance, Similarity Determining System 100 will receive at least
two search terms, i.e., one or more Fields from a sScond Entity and
compare these Fields to the first Entity, the Similarity
Determining System 100 further displaying the matching Fields in
descending order, block 228. Of course, descending order is merely
exemplary of one form of display, alternatives such as ascending,
scaled size, color or other ordering or visual queue being selected
and applied as appropriate for varying embodiments.
[0104] Moreover, the User or system may define Interest Groups
defined to be specifically at least two Fields which are used in
context with one another. For example a User may define "Surfing"
and "Beaches" as an Interest Group or "Marathon," "Disney," and
"Running" as another Interest Group. Alternatively the system may
recognize at least the top two or more Fields in a Discussion or
Community and form an Interest Group automatically for that
Discussion or Community. Determinations of Similarity may then be
performed by receiving an Interest Group, i.e. at least two
associated Fields, and may be performed by looking for other
Entities with similar Interests Groups.
[0105] In another example, Interest Groups can allow for setting
over visibility, connectivity, and privacy between Entities, for
example, if a user has an Interest Group that includes the
interests "Surfing" "Beaches" "Mexico" "Summer" then this user can
use this Interest group to limit their connections to similar
entities; i.e. people, posts, discussions, groups, communities,
etc. that share similar Fields.
[0106] Indeed for at least one embodiment, a Field can be
recognized as an Entity--as a Field builds associations to other
Fields through their shared associations to other Entities. For
instance, if a User has as association to "Surfing" and "Beaches"
and "Mexico" the Field "Surfing" would be an Entity that has an
association to "Beaches" and "Mexico" for that User. In other words
the context of association of one field to another advantageously
permits not only identification of similarity, but also the correct
context between Fields--i.e., the Field Jaguar in a Discussion
about sports teams is significantly different from the Field Jaguar
in a Discussion about jungle cats. Similarly, expressions such as
"Hot Dog" can be contextually determined based on Discussion to be
a food, a canine with an elevated temperature, or perhaps an
expression of amazement.
[0107] Likewise, it may be assumed that a User Entity with a number
of Fields that relate to sports, or more specifically, the National
Football League, has a higher probability of using the term Jaguars
as it relates to the football team, over Jaguars that may relate to
the Jungle cat or the luxury vehicle. For a community dedicated to
food, there is a higher probability that the word "Hot Dog" refers
to the food rather than a canine with an elevated blood
pressure.
[0108] This is fundamentally different from searching for a first
term within X words or characters of a second term, as the analysis
is driven directly by associated contextual use of the fields and
not by the arbitrary notion that if used within X the terms must be
related. Indeed embodiments of the present invention can establish
contextual relationships to be understood with advantageous scope
that transcends individual instances of use of the terms and
permits contextual awareness with respect to Entities of different
types.
[0109] In addition, this advantageous ability to determine the
context of fields may for at least one embodiment includes the use
of pronouns, which are understood and appreciated to be words that
take the place of a noun. For example, an first posting "the
Bronco's are great and this year Payton is going to see them all
the way to the Super Bowl" might be followed up by a posting "For
sure--they are great and he is best!" In this subsequent posting
the fields Bronco's and Payton have been replaced by pronouns they
and he. These pronouns are not general fields that build value
independently through subsequent use, but are instead trapped by
Similarity Determining System 100 as sub-fields because of their
proximity to the posting with the initial Fields.
[0110] With the response evaluated, and an indication of Field
Values provided, method 200 will optionally return to a monitoring
state, block 206, or end, decision 230. It should be understood and
appreciated that method 200 may be applied recursively. Moreover,
each response can be used as a trigger to initiate for that
particular User and associated Entities the application of method
200 to develop valuation for Fields based on subsequent
responses.
[0111] With respect to the evaluation process, this can occur in
real time, or through an assessment of archived data.
[0112] FIG. 4 conceptually illustrates at least a portion of
Discussion 400 that has evolved on a Social Network site, e.g.,
first Social Network 102--which for the sake of example is
presented as a University's Social Network site where students and
faculty can discuss ideas. For each Entry/Response of the
Discussion 400, method 200 is applied as described above.
[0113] To summarize, the method 200 as applied to Discussion 400 in
FIG. 4 is implemented by gathering metadata from at least one
posting by a first User to define at least one first Field
associated with at least one first Entity, each First Field having
a value. Method 200 continues by evaluating responses to the
posting by at least one Third Party, and in response to the Third
Party using one or more of the First Fields, incrementing the value
of each used First Field. And method 200 provides an indication of
the values of each First Field associated with each First Entity,
the indicated values permitting a determination of similarity to at
least one Second Entity querying for at least two Fields.
[0114] Returning to FIG. 4, there are shown to be four registered
Users--Prof. Spiff Jones, who has commenced Discussion 402
regarding Einstein's greatest contribution, and provided an opening
post 404, and Mark, Jill and Dan who have each provided a response,
406, 408 and 410 respectively.
[0115] FIG. 4 also provides a conceptual illustration of the Field
collections for at least the Entities 450 of the community--MTT
University 452, a sub-community--Intro science 454, a
Discussion--Einstein's Greatest Contribution 456, and collections
for each User--Spiff Jones 458, Mark 460, Jill 462 and Dan 464. The
hierarchy of the Entities 450 is also shown.
[0116] As shown in Bold, at least the words Einstein and Physics
are identified as Fields 412 and associated with Spiff Jones.
Likewise, Users Mark, Jill and Dan each have associated Fields that
are shown to have accumulated Field Values based on subsequent
replies from other Users. For at least one embodiment, Field Value
is determined simply by frequency of use. For at least one
embodiment, Field Value is determined simply by frequency of
Response and/or frequency of Response by unique users. For at least
one alternative embodiment, Field Value is determined by at least
one method set forth in application Ser. No. 13/239,100, which is
to say that the type of response (direct or indirect) Field average
and/or weighting may be applied so as to better harmonize the
values for improved determinations between large and small
instances of use.
[0117] More specifically, it is appreciated from FIG. 3 that the
Field Values developed with respect to each User's Entry/Response
and shown for each User's Entry/Response Collection are accumulated
for the Discussion 456. Likewise, additional Discussions that are
not shown also have accumulated Field Values and are combined for
the Field Values shown for the sub-community Intro science 454. And
similarly, multiple sub-communities are combined for the Field
Values of the overall Community MTT University 452.
[0118] For at least one embodiment, a Field that is not used for a
period of time may have its Field Value dissipated. This may be
achieved by the application of an automatic decay process, such as
but not limited to an evaluation directed by a command, if Field
not used for 200 days, reduce Field Value by 0.1%. Of course the
decay process may be applied in different ways--if the discussion
itself is dormant, then no decay is applied--the Fields and Field
Values having been established as expected and relevant future use
unrelated to the original discussion. However, if the discussion is
alive and on-going but a Field is no longer in active use, then
apply the decay process to dissipate the accumulated Field Value
over time.
[0119] FIG. 5 presents more clearly a plurality of different tables
associating the Fields to different Entities. More specifically,
table of records 500 shows the Field Values developed for each of
the Users. As shown, there are entries for Field Values for Fields
used by the User Spiff in column 502, Mark in Column 504, Jill in
column 506 and Dan in column 508.
[0120] In addition, table of records 510 shows the Field Values
developed for the Entity defined as the Discussion 456. Table of
records 512 shows the Field Values developed for the Entity defined
as the sub-Community, Intro science 454, and table of records 514
shows the Field of Values developed for the Entity defined as the
Community MTT University 452.
[0121] In addition, table of records 516 shows the Field Values
developed for sub-Community Intro science 454 based on all
Discussions, occurring within that sub Community, and table of
values 518 shows the Field Values developed for the parent
Community MTT University 452 based on all Discussions that occurred
within all sub-Communities of MTT University.
[0122] Moreover, with respect to the Discussion 400, the developed
Field Values are shown with respect to several different Entities
of varying scope. With respect to the issue of determining
similarity, any one may be considered as a first Entity for
comparison with a Second Entity. More specifically, for at least
one embodiment, a first Entity is selected from the group
consisting of, but not limited to, the first User starting
initiating the Discussion, the Posting by the first User, the First
Social Network, a Community, a Second Social Network, a First
Discussion, a Second Discussion, or an Interest (as in a specific
Field).
[0123] Of course the Second Entity may also be selected from the
group consisting of, but not limited to, a Third Party responding
to the First User, the Response by the Third Party, the First
Social Network, a Community, a Second Social Network, a first
Discussion, a Second Discussion, a social media object, or an
Interest (as in a specific Field). Moreover, the First Entity and
the Second Entity may be any of the different possible Entities
that may be recognized by an embodiment of the Similarity
Determining System 100. Of course it is understood and appreciated
that the First Entity and the Second Entity are distinct from each
other--which is to say that they are not one and the same
Entity.
[0124] For the sake of example, a User of Similarity Determining
System 100 may indicate that the Discussion 302 is to be the First
Entity and he or she is seeking to better gage the level of
similarity between this discussion and the total sub-Community of
Intro Science and or the total Community MTT University.
Accordingly for a first instance the second Entity is Intro
Science, and for a second instance the second Entity is MTT
University.
[0125] With respect to table of values 516 and table of values 518,
the Fields originating with the exemplary Discussion 300 are shown
in bold so as to indicate how the Fields relate in the overall
totals. Moreover, a User of Similarity Determining System 100 is
provided with a visual indication of how Fields relate and can
therefore assess the degree of similarity as between the exemplary
Discussion 300 as it relates to the overall totals of the sub
community for Intro Science and the overall totals of the community
MTT University.
[0126] Of course, for the exemplary Discussion 400 shown in FIG. 4,
the determination of similarity between the Users and illustrated
Entities is somewhat already self evident as the Users are
themselves actively engaging in the exemplary Discussion. The
advantageous nature of the Similarity Determining System 100 and
method 200 is more fully appreciated with respect to the
determination of similarity with other Entities not directly party
to the exemplary discussion 400, and/or perceiving other
similarities with Entities beyond the context of discussion
400.
[0127] FIG. 6 therefore conceptually illustrates at least a portion
of different Discussion 600 that has evolved on a Social Network
site. This Discussion 600 may have evolved on the same Social
Network site 102 as Discussion 400 or a different Social Network
site, i.e., Social Network site 112.
[0128] As with Discussion 400, in Discussion 600 there are a
plurality of Users--Prof. Spiff Jones, who has commenced the
discussion 602 regarding Einstein, e=mc.sup.2, Nuclear Power and
Nuclear Weapons, and provided an opening post 404, and Dan_Man,
Steve and Rick who have each provided a response, 606, 608 and 610
respectively.
[0129] Whereas Discussion 400 was for the sake of example analyzed
by the Similarity Determining System 100 in substantially real
time, Discussion 600 is understood and appreciated to be analyzed
by the Similarity Determining System 100 after occurring. Moreover,
it is understood and appreciated that the Similarity Determining
System 100 can be applied historically, which is to say to
preexisting or archived discussions so as to identify Fields and
area of Similarity between existing Entities.
[0130] In addition, Similarity Determining System 100 can evaluate
a Discussion, such as Discussion 400 or Discussion 600 to provide
values and still remain active to detect and account for subsequent
responses by Users occurring after the initial evaluation for
similarity has been performed. Moreover, Similarity Determining
System 100 and method 200 are understood and appreciated to be
ongoing systems and methods, operating to potentially rest at
times, but able to account for new Entries/Responses when and as
added.
[0131] Moreover, for historical review and analysis method 200 is
applied substantially as described above, however the actions of
monitoring for Entry/Response, block 206 becomes the action of
stepping through each Entry/Response as they have already been
provided and no waiting time is required. Similarly, invitations to
become a registered User, decision 210, may be skipped.
[0132] To summarize, the method 200 as applied to Discussion 600 in
FIG. 6 is implemented by establishing a Database of Fields
collected, from a first Discussion on a first Social Network, the
Discussion including a plurality of postings by at least one first
User and at least one second User, the Fields associated with at
least a first Entity. Method 200 continues by assigning a value to
each Field, and evaluating the values of each Field to one another
to establish a first Table providing a context of association
between Fields to identify the First Entity has having a quantified
level interests as identified by each Field, the values permitting
a determination of similarity to at least one Second Entity
querying for at least two Fields.
[0133] FIG. 6 also shows a conceptual illustration of the Field
Collections for at least the Entities 650 of the
Community--Megathread Post 652. The sub-community--Science Section
654, a discussion--Einstein, e=mc.sup.2, Nuclear Power and Nuclear
Weapons 656, and a collection of Users--Spiff Jones 658, Dan_Man
660, Steve 662 and Rick 664. The hierarchy of the Entities 650 is
also shown.
[0134] As shown in Bold, at least the words, e=mc.sup.2,
mass-energy equivalence, nuclear power and nuclear weapons are
identified as Fields 612 and associated with Spiff Jones. Likewise,
Users Dan_Man, Steve and Rick each have associated Fields which are
shown to have accumulated Field Values based on subsequent replies
from other Users.
[0135] More specifically, it is appreciated from FIG. 6 that the
Field Values developed with respect to each User's Entry/Response
and shown for each User's Entry/Response Collection are accumulated
for the Discussion 656. Likewise, additional Discussions that are
not shown also have accumulated Field Values and are combined for
the Field Values shown for the sub-community Science Section 654.
And similarly, multiple sub-communities are combined for the Field
Values of the overall Community Megathread Post 652.
[0136] FIG. 7 presents more clearly a plurality of different tables
associating the Fields to different Entities. More specifically,
table of records 700 shows the Field Values developed for each of
the Users. As shown, there are entries for Field Values for Fields
used by the User Spiff in column 702, Dan_Man in Column 704, Steve
in column 706 and Rick in column 708.
[0137] In addition, table of records 710 shows the Field Values
developed for the Entity defined as the discussion 656. Table of
records 712 shows the Field Values developed for the Entity defined
as the sub-community, Science Section 654, and table of records 714
shows the Field of Values developed for the Entity defined as the
community Megathread Post 652.
[0138] In addition, table of records 716 shows the Field Values
developed for sub-community Science Section 654 based on all
discussions, and table of values 718 shows the Field Values
developed for the total community Megathread Post 652 based on all
discussions.
[0139] Fields and more specifically Field Values are cumulative,
such that the Fields and Field Values earned by an Entity in one
Discussion are aggregated with the Fields and Field Values earned
by that same Entity with respect to other Discussions.
[0140] Moreover, as shown in FIG. 8, User Dan_Man has accumulated
Field Values 704 from Discussion 700 which are aggregated with his
other Fields from other Discussions not shown, to provide a total
or global table 800 of associated Fields and values for User
Dan_Man. Likewise User Spiff (having the aliases Dr. Spiff Jones
and Prof. Spiff Jones) has accumulated Field Values 502 from
Discussion 400 and Field Values 702 from Discussion 700 which in
turn are aggregated with his other discussions to yield a total or
global table 802 of associated Fields and Values for User
Spiff.
[0141] Indeed, for at least one embodiment each Entity's global
table is the table selected for similarity detection. For example,
FIG. 9 illustrates several global tables duplicated from FIGS. 5, 7
and 8--those tables on the left corresponding to the Entities
involved in Discussion 400, i.e., the community--MTT University
518, the sub-community--Intro science 516, the
discussion--Einstein's Greatest Contribution 510 and User--Spiff
802. On the right are the global tables corresponding to Entities
involved in Discussion 600, i.e., the community--Megathread Post
718, the discussion--Einstein, e=mc.sup.2, Nuclear Power and
Nuclear Weapons 712, and User Dan_Man 800.
[0142] As has been noted repeatedly above, for at least one
embodiment a higher order Entity, such as but not limited to a
Community, or a social media object such as a Discussion will
develop Field Value through the aggregation of the lower order
Entities. This advantageous nature is reiterated in FIG. 10 and in
the context of the above discussion may be more fully appreciated
now. Moreover, in FIG. 10 the exemplary discussion 1000 may be
appreciated to develop Field Value for Fields associated with the
social media object Entity identified as Megathread Resorts 1002.
Clearly Megathread Resorts 1002 is not a human Entity, but through
the advantageous systems and methods permitted by Similarity
Determining System 100, develops Field Values for associated Fields
that can be of significant value to potential guests of Megathread
Resorts 1002. Moreover, in FIG. 10, the Social Media Object/Entity
Megathread Resorts 1002 generates its Fields and Field Values 1004
through the aggregation of Fields and Field Values of the lower
level entities associated with that discussion (i.e. the
Entry/Response by the users of the Discussion(s) 1000 pertaining to
Megathread Resorts 1002.) This same example can be applied to any
form of Social Media Object/Entity which directly relates to the
Discussion (i.e. a picture, video, song, product, service,
advertisement, etc.)
[0143] As indicated by arrows 900 Similarity Determining System 100
is indicating several different connections of similarity. As
shown, similarity between a first Entity and a Second Entity is
determined at least in part by comparing the First Entity Table
with the Second Entity Table so as to identify matching Fields as
well as the relationships between those Fields. More specifically,
User Dan_Man, who has a significant interest in the equation
e=mc.sup.2, Physics, and Science but who has never visited the
first Social Network 102, is advantageously permitted by Similarity
Determining System 100 to identify other Entities who share similar
interests.
[0144] Again, as an Interest Group is defined as two or more
associated Fields, similarity may be determined in at least one
embodiment by specifically utilizing an Interest Group, defined
either by the User, the Community or the Similarity Determining
System 100.
[0145] With respect to the above descriptions regarding Discussions
400 and 600, it should also be understood and appreciated that for
at least one embodiment Similarity Determining System 100 is
operable to develop Fields and Field Values for multiple Entities
about contemporaneously. Moreover, method 200 can be adapted to be
applied generally simultaneously for both a first Entity and a
second Entity.
[0146] To summarize for either Discussion 400 or Discussion 600, in
at least one embodiment, Similarity Determining System 100 gathers
metadata from at least one posting by a first User on a first
Social Network 102 to define at least one first Field associated
with at least one first Entity, each associated first Field having
a value.
[0147] Similarity Determining System 100 continues with gathering
metadata from at least one Third Party response to the posting by
the first User to define at least one second Field associated with
at least one second Entity, each associated second Field having a
value.
[0148] The gathered metadata form the Third Party is response
relating to the posting by the first User is evaluated to increment
the value of at least one first Field as associated with the first
Entity. Substantially the same action is performed for yet another
Third Party response relating to the first Third Party response. An
indication of the value of each first Field and each second Field
associated with each first Entity and second Entity to indicate a
value of similarity between each first Entity and second
Entity.
[0149] With respect to the above description of similarity
determination, it should be understood and appreciated that
Similarity Determining System 100 advantageously permits even new
Users to quickly identify other Entities with which he or she
shares common interests (defined as Fields.) Indeed, for at least
one embodiment, the Similarity Determining System 100 permits a
User to manually enter at least two Fields directly for query
without having a pre-established table of Fields and associated
values. As such, a User wishing to identify Entities with useful
information can be quickly identified with greater context then is
generally permitted with a more free form web search.
[0150] With respect to the above description of similarity
determination, it should be understood and appreciated that
Similarity Determining System 100 advantageously permits Individual
Users, Communities Administrators, and Automated settings over
privacy, visibility and accessibility between entities. Such that
Entities can be protected from irrelevant connections while
simultaneously provided increased relevance between similar
Entities. While the Similarity Determining System is primarily
based upon Entities defined by associated Fields and their Values,
these credentials can be used to provide access or improve other
technologies that can be seen as external Entities, such as
advertisements, job placements, analysis, search engines, skill
sharing, credential systems such as badges, etc.
[0151] It should also be understood and appreciated that as the
method 200 of Authentication bridges the registered Users identity
across multiple Social Networks, it is advantageously possible for
an inquisitive party to learn of other discussions and or
information upon other Social Networks that he or she may have been
previously unaware of. For example, a person looking for
information in caring for an elderly parent may discover a Social
Network and support group that is entirely dedicated to that cause.
Likewise, a universe of valuable information regarding nut
allergies, ideas for safe birthday ideas for children, or other
issues may be easily identified and accessed in ways that are not
currently provided by traditional search engines.
[0152] With respect to the above description of Similarity
Determining System 100 and method 200 it is understood and
appreciated that the method may be rendered in a variety of
different forms of code and instruction as may be used for
different computer systems and environments. To expand upon the
initial suggestion of a computer implementation above, FIG. 11 is a
high level block diagram of an exemplary computer system 1100.
Computer system 1100 has a case 1102, enclosing a main board 1104.
The main board 1104 has a system bus 1106, connection ports 1108, a
processing unit, such as Central Processing Unit (CPU) 1110 with at
least one microprocessor (not shown) and a memory storage device,
such as main memory 1112, hard drive 1114 and CD/DVD ROM drive
1116.
[0153] Memory bus 1118 couples main memory 1112 to the CPU 1110. A
system bus 1106 couples the hard disc drive 1114, CD/DVD ROM drive
1116 and connection ports 1108 to the CPU 1110. Multiple input
devices may be provided, such as, for example, a mouse 1120 and
keyboard 1122. Multiple output devices may also be provided, such
as, for example, a video monitor 1124 and a printer (not
shown).
[0154] Computer system 1100 may be a commercially available system,
such as a desktop workstation unit provided by IBM, Dell Computers,
Gateway, Apple, or other computer system provider. Computer system
1100 may also be a networked computer system, wherein memory
storage components such as hard drive 1114, additional CPUs 1010
and output devices such as printers are provided by physically
separate computer systems commonly connected together in the
network. Those skilled in the art will understand and appreciate
that the physical composition of components and component
interconnections are comprised by the computer system 1100, and
select a computer system 1000 suitable for the establishing the
Authentication System 100.
[0155] When computer system 1100 is activated, preferably an
operating system 1126 will load into main memory 1112 as part of
the boot strap startup sequence and ready the computer system 1100
for operation. At the simplest level, and in the most general
sense, the tasks of an operating system fall into specific
categories, such as, process management, device management
(including application and User interface management) and memory
management, for example. The form of the computer-readable medium
1128 and language of the program 1130 are understood to be
appropriate for and functionally cooperate with the computer system
1100.
[0156] Changes may be made in the above methods, systems and
structures without departing from the scope hereof. It should thus
be noted that the matter contained in the above description and/or
shown in the accompanying drawings should be interpreted as
illustrative and not in a limiting sense. The following claims are
intended to cover all generic and specific features described
herein, as well as all statements of the scope of the present
method, system and structure, which, as a matter of language, might
be said to fall there between.
* * * * *