IP Library › Granted Patent US 10,101,820
Granted Patent B2
US 10,101,820 · App. 15/216,060 · Granted Oct 16, 2018

Automated learning and gesture based interest processing

Inventors: Thomas E. Creamer (Boca Raton, FL); Erik H. Katzen (Argyle, TX); Sumit Patel (Round Rock, TX)
Assignee: International Business Machines Corporation
G06F3/017G06F17/3053G06F17/30598G06K9/66
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Quick Facts
Patent No.
US 10,101,820
App. No.
15/216,060
Granted
Oct 16, 2018
Kind
B2
Abstract

A system, method and program product for processing user interests. A system is provided that includes: a gesture management system that receives gesture data from a collection device for an inputted interest of a user; a pattern detection system that receives and analyzes behavior data associated with the inputted interest; an interest affinity scoring system that calculates an affinity score for the inputted interest based on the gesture data and an analysis of the behavior data; a dynamic classification system that assigns a dynamically generated tag to the inputted interest based on an inputted context associated with the inputted interest; and a user interest database that stores structured interest information for the user, including a unique record for the inputted interest that includes the affinity score and dynamically generated tag.

Claims (26)

1. A system for processing user interests, comprising:

an interface for receiving an inputted interest and an inputted context from a user, wherein the inputted context includes a natural language input;

a gesture management system that receives gesture data from a collection device with the inputted interest to identify a gesture from a set of gestures predefined by the user;

a pattern detection system that receives behavior data associated with the inputted interest and determines whether the behavior data includes a recognized behavior pattern based on previously collected behavior data of the user, in which the recognized behavior pattern was not predefined by the user;

an interest affinity scoring system that calculates an affinity score for the inputted interest based on an identified gesture and a recognized behavior pattern;

a dynamic classification system that assigns a dynamically generated tag to the inputted interest based on the natural language input; and

a user interest database that stores structured interest information for the user, including a unique record for the inputted interest that includes the affinity score and dynamically generated tag.

2. The system of claim 1 , wherein each gesture in the set of set of gestures defined by the user includes a first indicator of relevance to the user.

3. The system of claim 2 , wherein previously collected behavior data is stored in a user interest database.

4. The system of claim 3 , wherein recognized behavior patterns are correlated by a learning system with a second indicator of relevance to the user.

5. The system of claim 4 , wherein the interest affinity scoring system utilizes the first indicator of relevance and the second indicator of relevance to calculate the affinity score.

6. The system of claim 1 , wherein the natural language input is used to form the dynamically generated tag.

7. The system of claim 1 , wherein the dynamically generated tag and affinity score are periodically reevaluated and updated in response to a received additional inputted context associated with the inputted interest.

8. A computer program product stored on a computer readable storage medium, which when executed by a computing system, processes user interests, the program product comprising:

program code for receiving an inputted interest from a user and an inputted context, wherein the inputted context includes at least one of a natural language input, a time parameter and a location parameter;

program code that receives gesture data from a collection device with the inputted interest to identify a gesture from a set of gestures predefined by the user;

program code that receives behavior data associated with the inputted interest and determines whether the behavior data includes a recognized behavior pattern based on previously collected behavior data of the user, in which the recognized behavior pattern was not predefined by the user;

program code that calculates an affinity score for the inputted interest based on an identified gesture and a recognized behavior pattern;

program code that assigns a dynamically generated tag to the inputted interest based on the inputted context associated with the inputted interest; and

program code that stores structured interest information for the user, including a unique record for the inputted interest that includes the affinity score and dynamically generated tag.

9. The program product of claim 8 , wherein each gesture in the set of gestures defined by the user includes a first indicator of relevance to the user.

10. The program product of claim 9 , wherein previously collected behavior data is stored in a user interest database.

11. The program product of claim 10 , wherein recognized behavior patterns are correlated by a learning system with a second indicator of relevance to the user.

12. The program product of claim 11 , further comprising program code that utilizes the first indicator of relevance and the second indicator of relevance to calculate the affinity score.

13. The program product of claim 8 , code wherein natural language input is used to form the dynamically generated tag.

14. The program product of claim 8 , wherein the dynamically generated tag and affinity score are periodically reevaluated and updated in response to a received additional inputted context associated with the inputted interest.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 21, 2016
From: CREAMER, THOMAS E.; KATZEN, ERIK H.; PATEL, SUMIT
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 039214/0011 →
Continuity (1)
Related Publication 20180024639A1 · Jan 25, 2018