Receiving and Correlation of User Choices to Facilitate Recommendations for Peer-to-Peer Connections

• US 20130339445A1
• Filed: 06/14/2013
• Published: 12/19/2013
• Est. Priority Date: 06/14/2012
• Status: Active Grant

• Current Assignee: Discourse Analytics, Inc.
• Original Assignee: Discourse Analytics, Inc.
• Inventors: Perincherry, Vijay
• Granted Patent: US 9,344,519 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 30/0237 at kiosk
• CPC Class Codes: G06Q 30/0239 Online discounts or incentives
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data

Abstract

Systems, methods, and computer program products are disclosed which facilitate collecting information about users, including responses to poll prompts, and analyzing such information in order to determine correlations and inter-relationships of information and information areas. In an aspect, information from many users is collected across a variety of user interaction channels and computing device platforms. Such information is analyzed in order to generate profiles of like-minded individuals. Such profiles may be useful for recommending peer-to-peer connection between individuals, marketing products and services to individuals with similar attributes and traits, and examining changes in individual preferences over time or in response to external factors.

Claims

1. A computer-implemented method for facilitating identification of correlations in user data, the method comprising the steps of:

(a) receiving user opinions from a plurality of users, the user opinions relating to a topic;

(b) receiving a plurality of attribute sets, each of the plurality of attribute sets comprising user information from a plurality of users related to one of a plurality of attribute subjects;

(c) selecting a subset comprising at least one of the plurality of attribute sets;

(d) creating at least one grouping, each grouping comprising user information associated with each of the at least one of the plurality of attribute sets comprising the subset;

(e) creating a user opinion distribution of the user opinions associated with the at least one grouping;

(f) calculating the user opinion uncertainty of the user opinion distribution;

(g) determining if the user opinion uncertainty is less than a user opinion threshold value; and

(h) identifying, if determining step (g) is positive, the at least one grouping as correlating with user opinions for the topic.

2. The method of claim 1, further comprising the steps of:

(i) calculating a user opinion distribution mean;

(j) creating an at least one grouping distribution;

(k) calculating an at least one grouping distribution mean;

(l) comparing the user opinion distribution mean and the at least one grouping distribution mean; and

(m) where the comparison of the user opinion distribution mean and the at least one grouping distribution mean is statistically significant, discarding the at least one grouping.

3. The method of claim 1, wherein the user opinions are received from the plurality of users via at least one poll presented via a plurality of computing devices.

4. The method of claim 3, wherein the plurality of users are presented with a plurality of polls over time.

5. The method of claim 1, further comprising the step of:

(n) presenting targeted information to a group member;

wherein the group member has attributes associated with the identified at least one grouping.

6. The method of claim 5, wherein the targeted information is chosen based on the user opinions associated with the identified at least one grouping.

7. The method of claim 5, wherein the targeted information is one of:

an advertisement;

a coupon;

a customer engagement message;

an advocacy message; and

a political message.

8. A system for facilitating identification of correlations in user data, comprising:

(a) at least one web server capable of providing a graphical user interface, via a communications network, to a plurality of computing devices, the plurality of computing devices configured to communicate with a plurality of users;

(b) at least one user communication service, communicatively coupled to the at least one web service via the communications network, the at least one user communication service comprising;

a user database comprising user opinions received from a plurality of users, the user opinions relating to a topic;

(c) at least one application server, communicatively coupled to the at least one web server via the communications network, the at least one application server comprising;

(i) an attribute set database comprising a plurality of attribute sets, each of the plurality of attribute sets comprising user information from a plurality of users related to one of a plurality of attribute subjects;

(ii) a selection service capable of selecting a subset comprising at least one of the plurality of attribute sets;

(iii) a group service capable of creating at least one grouping, each grouping comprising user information associated with each of the at least one of the plurality of attribute sets comprising the subset;

(iv) a distribution service capable of creating a user opinion distribution of the user opinions associated with the at least one grouping;

(vi) an analysis service, capable of calculating a user opinion uncertainty of the user opinion distribution and determining if the user opinion uncertainty is less than a user opinion threshold value; and

(vii) a correlation database capable of storing the at least one grouping when the user opinion uncertainty is less than the user opinion threshold value;

wherein the at least one grouping stored in the correlation database correlates with user opinions for the topic.

9. The system of claim 8, the at least one application server further comprising:

(viii) a mean analysis service, capable of calculating a user opinion distribution mean, calculating an at least one grouping distribution, and comparing the user opinion distribution mean and the at least one grouping distribution mean;

wherein, if the comparison of the user opinion distribution mean and the at least one grouping distribution mean is statistically significant, the at least one grouping is not stored in the correlation database.

10. The system of claim 8, wherein the user database is further configured to receive user opinions provided via a plurality of computing devices.

11. The system of claim 10, further comprising:

(d) at least one poll server, communicatively coupled to the at least one web server via the communications network, capable of presenting the plurality of users with a plurality of polls over time.

12. The system of claim 8 further comprising:

(e) at least one presentation server, communicatively coupled to the at least one web server via the communications network, capable of presenting targeted information to a group member via the plurality of computing devices;

wherein the group member has attributes associated with the identified at least one grouping.

13. The system of claim 12, wherein the targeted information is chosen based on the user opinions associated with the identified at least one grouping.

14. One or more computer storage media having stored thereon multiple instructions that facilitate identification of correlations in user data by, when executed by one or more processors of a computing device, causing the one or more processors to:

(a) receive user opinions from a plurality of users, the user opinions relating to a topic;

(b) receive a plurality of attribute sets, each of the plurality of attribute sets comprising user information from a plurality of users related to one of a plurality of attribute subjects;

(c) select a subset comprising at least one of the plurality of attribute sets;

(d) create at least one grouping, each grouping comprising user information associated with each of the at least one of the plurality of attribute sets comprising the subset;

(e) create a user opinion distribution of the user opinions associated with the at least one grouping;

(f) calculate the user opinion uncertainty of the user opinion distribution;

(g) determine if the user opinion uncertainty is less than a user opinion threshold value; and

(h) identify, where the user opinion uncertainty is less than the user opinion threshold value, the at least one grouping as correlating with user opinions for the topic.

15. One or more computer storage media as recited in claim 14, wherein the multiple instructions further cause one or more processors to:

(i) calculate a user opinion distribution mean;

(j) create an at least one grouping distribution;

(k) calculate an at least one grouping distribution mean;

(l) compare the user opinion distribution mean and the at least one grouping distribution mean; and

(m) where the comparison of the user opinion distribution mean and the at least one grouping distribution mean is statistically significant, discard the at least one grouping.

16. One or more computer storage media as recited in claim 14, wherein the user opinions are received from the plurality of users via at least one poll presented via a plurality of computing devices.

17. One or more computer storage media as recited in claim 14, wherein the multiple instructions further cause one or more processors to:

(n) present targeted information to a group member;

wherein the group member has attributes associated with the identified at least one grouping.

18. A computer-implemented method for facilitating peer-to-peer connections based on correlations of user data, the method comprising the steps of:

(a) creating a first multi-dimensional user profile comprising;

(i) user K opinions received from a user K, relating to a topic; and

(ii) user K information received from the user K, relating to at least one attribute subject;

(b) creating a second multi-dimensional user profile comprising;

(i) user L opinions received from a user L, relating to the topic; and

(ii) user L information received from the user L, relating to the at least one attribute subject;

(c) comparing the first multi-dimensional user profile and the second multi-dimensional user profile;

(d) presenting the second multi-dimensional user profile to the user L where the comparison of the first multi-dimensional user profile and the second multi-dimensional user profile yields similarities in one of;

interest level in the topic; and

user K opinion and user L opinion.

19. The method of claim 18, further comprising the step of:

(e) presenting a user K summary to the user L, the user K summary comprising at least one graphical representation of user K opinions and similarities in one of;

interest level in the topic; and

user K opinion and user L opinion.

20. The method of claim 18, further comprising the step of:

(f) facilitating communication between the user K and the user L.

21. A system for facilitating peer-to-peer connections based on correlations of user data, comprising:

(a) at least one web server capable of providing a graphical user interface, via a communications network, to a plurality of computing devices;

(b) at least one user communication service, communicatively coupled to the at least one web service via the communications network, the at least one user communication service comprising;

a user database comprising user opinions received from a plurality of users, the user opinions relating to a topic;

(c) at least one profile server, communicatively coupled to the at least one web service via the communications network, the at least one profile service comprising;

(i) a profile database configured to store a first multi-dimensional user profile and a second multi-dimensional user profile;

(ii) a profile creation service capable of creating and storing on the profile database, the first multi-dimensional user profile comprising;

(A) user K opinions received from a user K, relating to a topic; and

(B) user K information received from the user K, relating to at least one attribute subject; and

capable of creating and storing on the profile database, the second multi-dimensional user profile comprising;

(C) user L opinions received from a user L, relating to the topic; and

(D) user L information received from the user L, relating to the at least one attribute subject;

(iii) a comparison service capable of comparing the first multi-dimensional user profile and the second multi-dimensional user profile;

(iv) at least one profile presentation server, communicatively coupled to the at least one web server via the communications network, capable of presenting the second multi-dimensional user profile to the user K where the comparison of the first multi-dimensional user profile and the second multi-dimensional user profile yields similarities in one of;

interest level in the topic; and

the user L opinion and the user K opinion.

22. The system of claim 21, wherein the at least one profile presentation service is further capable of presenting a first user summary to the user L, the first user summary comprising at least one graphical representation of the user L opinions and similarities in one of:

interest level in the topic; and

the user L opinion and the user K opinion.

23. The system of claim 21, further comprising:

(f) at least one user communication server, communicatively coupled to the at least one web service via the communications network, the at least one communication server capable of facilitating communication between the user K and the user L.

24. One or more computer storage media having stored thereon multiple instructions that facilitate peer-to-peer connections based on correlations of user data by, when executed by one or more processors of a computing device, causing the one or more processors to:

(a) create a first multi-dimensional user profile comprising;

(i) user K opinions received from a user K, relating to a topic; and

(ii) user K information received from the user K, relating to at least one attribute subject;

(b) create a second multi-dimensional user profile comprising;

(i) user L opinions received from a user L, relating to the topic; and

(ii) user L information received from the user L, relating to the at least one attribute subject;

(c) compare the first multi-dimensional user profile and the second multi-dimensional user profile;

(d) present the second multi-dimensional user profile to the user K where the comparison of the first multi-dimensional user profile and the second multi-dimensional user profile yields similarities in one of;

interest level in the topic; and

user K opinion and user L opinion.

25. One or more computer storage media as recited in claim 24, wherein the multiple instructions further cause one or more processors to:

(e) present a user K summary to the user L, the user K summary comprising at least one graphical representation of user K opinions and similarities in one of;

interest level in the topic; and

user K opinion and user L opinion.

26. One or more computer storage media as recited in claim 24, wherein the multiple instructions further cause one or more processors to:

(f) facilitate communication between the user K and the user L.