SYSTEM AND METHOD FOR DETERMINING RELEVANCE RATINGS FOR KEYWORDS AND MATCHING USERS WITH CONTENT, ADVERTISING, AND OTHER USERS BASED ON KEYWORD RATINGS

• US 20090234727A1
• Filed: 03/12/2008
• Published: 09/17/2009
• Est. Priority Date: 03/12/2008
• Status: Abandoned Application

• Current Assignee: Field Report Incorporated
• Original Assignee: Field Report Incorporated
• Inventors: Petty, William
• Application Number:
  US12/047,229
• Publication Number:
  US 20090234727A1
• Time in Patent Office: Days
• US Class Current: 705/14.540
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06F 16/24534 Query rewriting; Transformation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0256 User search

Abstract

Systems and methods for determining relevance ratings for keywords associated with content are disclosed. A quantitative degree of relevance of keywords for a piece of content is determined by querying several reviewers. System users have a keyword record listing the keywords associated with content that a user has exhibited a threshold of interest in. Moreover, a cumulative value for the keywords is maintained by adding the degree of relevance of content keywords to the cumulative value of the keyword in the user'"'"'s record. By finding correspondences between keywords in a user'"'"'s record and keywords for pieces of content, advertisements, or other people using the system, a user'"'"'s interest may be determined, and recommendations for content, advertisements, and potential friends or business contacts may be made to the user.

Claims

1. A method of creating a searchable database of content, comprising:

receiving pieces of content;

storing the pieces of content;

identifying content keywords for each piece of content;

determining a global relevance score for each content keyword for each piece of content, wherein determining a global relevance score includes receiving reviewer relevance score information for each content keyword and utilizing the reviewer relevance score information to determine the global relevance score;

storing the global relevance score for each content keyword for each piece of content,

wherein the content keywords and associated global relevance scores are used in a search for content in the database.

2. The method of claim 1, wherein the pieces of content are selected from a group consisting of text-based content, image-based content, video-based content, and audio-based content.

3. The method of claim 1, wherein determining a global relevance score comprises:

requesting a minimum number of reviewers to review a first piece of content to provide a reviewer relevance score for each content keyword associated with the first piece of content;

calculating the global relevance score for each content keyword based upon the reviewer relevance scores.

4. The method of claim 3, wherein each global relevance score is based upon a credibility score for each of the reviewers.

5. The method of claim 3, further comprising modifying the global relevance score for each content keyword to adjust for reviewer bias.

6. The method of claim 1, wherein determining a global relevance score comprises using a computer program to calculate the global relevance score for each content keyword for a piece of content.

7. A method of creating a user keyword record associated with a user, comprising:

determining whether the user has reached a threshold of interest for an accessed piece of content;

adding content keywords associated with the accessed piece of content as user keywords to the user'"'"'s keyword record, if not already present in the user'"'"'s keyword record;

processing a cumulative value and a new relative strength value for each content keyword in the user'"'"'s keyword record based upon a global relevance score of each content keyword, a previous cumulative value, and a previous relative strength value associated with each content keyword in the user'"'"'s keyword record,

wherein the user keywords and corresponding new relative strength values are compared with content keywords and corresponding relative strength scores of a piece of content to determine content of interest to the user.

8. The method of claim 7, wherein processing a new cumulative value comprises summing the previous cumulative value and the global relevance score.

9. The method of claim 8, wherein processing a new relative strength value comprises scaling the new cumulative value of each user keyword by a sum of all new cumulative values.

10. The method of claim 7, wherein the threshold of interest for a text-based piece of content is reached when the user scrolls to the end of the text-based piece of content.

11. The method of claim 7, wherein the threshold of interest for a video-based piece of content is reached when the user watches to the end of the video-based piece of content.

12. The method of claim 7, wherein the threshold of interest for an audio-based piece of content is reached when the user listens to the end of the audio-based piece of content.

13. A method of creating an advertisement keyword record associated with an advertisement, comprising:

determining when a user shows interest in the advertisement;

adding user keywords associated with the user to the advertisement'"'"'s keyword record, if not already present in the advertisement'"'"'s keyword record;

processing a new cumulative value and a new relative strength value for each of the user keywords in the advertisement'"'"'s keyword record based upon a relative strength value of each user keyword and a previous cumulative value associated with the user keyword in the advertisement'"'"'s record.

14. The method of claim 13, wherein interest is shown in the advertisement when the user clicks on the advertisement or buys an advertised product or service.

15. A method of recommending a piece of content to a user, comprising:

comparing content keywords and corresponding relative strength scores associated with the piece of content to user keywords and corresponding relative strength values associated with the user;

determining if a minimum degree of correspondence is established;

recommending the piece of content to the user if the minimum degree of correspondence is established.

16. The method of claim 15, wherein a minimum degree of correspondence is established if a strongest user keyword matches a strongest content keyword, or a predetermined number of user keywords matches the same predetermined number of content keywords, wherein the predetermined number of user keywords and predetermined number of content keywords have a minimum predetermined relative strength.

17. A method of selecting advertisements to be shown to a user, comprising:

comparing advertisement keywords and corresponding relative strength values associated with the advertisement to user keywords and corresponding relative strength values associated with the user;

determining if a minimum degree of correspondence is established;

presenting the advertisement to the user if the minimum degree of correspondence is established.

18. The method of claim 17, wherein a minimum degree of correspondence is established if a strongest user keyword matches a strongest advertisement keyword, or a predetermined number of user keywords matches the same predetermined number of advertisement keywords, wherein the predetermined number of user keywords and predetermined number of advertisement keywords have a minimum predetermined relative strength.

19. A method of introducing people based upon keyword interests, comprising:

comparing a first user'"'"'s keywords and corresponding strength values to a second user'"'"'s keywords and corresponding strength values;

determining if a minimum degree of correspondence is established;

introducing the first user and the second user if the minimum degree of correspondence is established.

20. The method of claim 19, wherein a minimum degree of correspondence is established if a strongest user keyword of the first user matches a strongest user keyword of the second user, a strongest user keyword of the first user matches a user keyword of the second user having a relative strength score greater than a first predetermined number, or a second predetermined number of user keywords of the first user matches the same second predetermined number of user keywords of the second user, wherein the second predetermined number of user keywords of the first user and the second predetermined number of user keywords of the second user have a minimum predetermined relative strength.

21. A system, comprising:

a content database for storing pieces of content, content keywords associated with each piece of content, and a global relevance score and relative strength for each content keyword;

a user database for storing user information, user keywords, and a user cumulative value and a user relative strength value for each user keyword;

a communications module for requesting reviewers to review a particular piece of content and rate a degree of relevance of one or more content keywords;

a keyword rating module for calculating the global relevance score and relative strength of each content keyword and calculating the user cumulative value and user relative strength value for each user keyword;

a keyword comparison module for determining a first degree of correspondence between content keywords of a particular piece of content and user keywords for a targeted user based upon global relevance scores or relative strength for the content keywords and user cumulative values or user relative strength values for the user keywords of the targeted user,

wherein the system recommends one or more pieces of content having a minimum first degree of correspondence to the targeted user.

22. The system of claim 21, further comprising an advertisement database for storing advertisements, advertisement keywords associated with each advertisement, a cumulative relevance score and a relative strength score for each advertisement keyword, and wherein the keyword comparison module further determines a second degree of correspondence between advertisement keywords of a particular advertisement and user keywords for a targeted user based upon cumulative relevance scores or relative strength scores for the advertisement keywords and user cumulative values or user relative strength values for the user keywords, and further wherein the system recommends one or more advertisements having a minimum second degree of correspondence to be shown to the targeted user.

23. The system of claim 21, wherein the keyword comparison module further determines a third degree of correspondence between user keywords for a first user and user keywords for a second user based upon user cumulative values or user relative strength values for the first user'"'"'s keywords and user cumulative values or user relative strength values for the second user'"'"'s keywords, and further wherein the system recommends one or users having a minimum third degree of correspondence to be introduced to the targeted user.