AUTOMATED LEARNING AND GESTURE BASED INTEREST PROCESSING

• US 20180024639A1
• Filed: 07/21/2016
• Published: 01/25/2018
• Est. Priority Date: 07/21/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Creamer, Thomas E., Katzen, Erik H., Patel, Sumit
• Granted Patent: US 10,101,820 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 2203/011 Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16

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

1. A system for processing user interests, comprising:

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.

2. The system of claim 1, wherein the gesture management system determines if the gesture data includes a predefined gesture correlated to a first indicator of relevance to the user.

3. The system of claim 2, wherein the pattern detection system determines if the behavior data matches one of a set of patterns of known behaviors stored in the user interest database.

4. The system of claim 3, wherein each of the patterns is correlated 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 inputted context includes a natural language input that 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.

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 that receives gesture data from a collection device for an inputted interest of a user;

program code that receives and analyzes behavior data associated with the inputted interest;

program code that calculates an affinity score for the inputted interest based on the gesture data and an analysis of the behavior data;

program code that assigns a dynamically generated tag to the inputted interest based on an 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, further comprising program code that determines if the gesture data includes a predefined gesture correlated to a first indicator of relevance to the user.

10. The program product of claim 9, further comprising program code that determines if the behavior data matches one of a set of patterns of known behaviors stored in the user interest database.

11. The program product of claim 10, wherein each of the patterns is correlated 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 the inputted context includes a natural language input that 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.

15. A computerized method for processing user interests, comprising:

receiving gesture data from a collection device for an inputted interest of a user;

receiving and analyzing behavior data associated with the inputted interest;

calculating an affinity score for the inputted interest based on the gesture data and an analysis of the behavior data;

assigning a dynamically generated tag to the inputted interest based on an inputted context associated with the inputted interest; and

storing structured interest information for the user that includes a unique record for the inputted interest having the affinity score and dynamically generated tag.

16. The computerized method of claim 15, further comprising determining if the gesture data includes a predefined gesture correlated to a first indicator of relevance to the user.

17. The computerized method of claim 16, further comprising determining if the behavior data matches one of a set of patterns of known behaviors stored in a user interest database.

18. The computerized method of claim 17, wherein each of the patterns is correlated with a second indicator of relevance to the user.

19. The computerized method of claim 18, where the first indicator of relevance and the second indicator of relevance are used to calculate the affinity score.

20. The computerized method of claim 15, wherein the dynamically generated tag and affinity score are periodically reevaluated and updated.