PREDICTIVE SERVICE SYSTEMS USING EMOTION DETECTION

• US 20090234718A1
• Filed: 05/20/2009
• Published: 09/17/2009
• Est. Priority Date: 09/05/2000
• Status: Abandoned Application

• Current Assignee: Novell Intellectual Property Holdings, Inc. (Open Text Corporation)
• Original Assignee: Novell Incorporated (Open Text Corporation)
• Inventors: Green, Tammy
• Application Number:
  US12/469,615
• Publication Number:
  US 20090234718A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 50/10 Services

Abstract

A predictive service system can include a gathering service to gather user information, a semantic service to generate a semantic abstract for the user information, an emotion detection service to identify emotion-related information, and a predictive service to act on an actionable item that is created based on the user information, the semantic abstract, and the emotion-related information.

Claims

1. A predictive service system, comprising:

at least one gathering service operable to gather user information pertaining to at least one user;

at least one semantic service operable to generate at least one semantic abstract for the user information;

at least one emotion detection service operable to generate emotion-related information pertaining to the at least one user; and

at least one predictive service operable to act on at least one actionable item based at least in part on the user information, the at least one semantic abstract, and the emotion-related information.

2. The predictive service system of claim 1, further comprising an analysis module in communication with the at least one gathering service, the at least one semantic service, the at least one emotion detection service, and the at least one predictive service, wherein the analysis module is operable to create the at least one actionable item and send the at least one actionable item to the at least one predictive service.

3. The predictive service system of claim 1, wherein the at least one emotion detection service is further operable to classify the emotion-related information.

4. The predictive service system of claim 3, wherein the at least one emotion detection service is further operable to determine an emotion intensity level of the emotion-related information.

5. The predictive service system of claim 1, wherein the user information comprises at least one of a user document and a user event.

6. The predictive service system of claim 1, wherein the user information comprises information pertaining to a user content flow.

7. The predictive service system of claim 1, wherein the at least one actionable item comprises at least one of a user recommendation, a user suggestion, and a user tip.

8. The predictive service system of claim 1, wherein the user information is gathered from a user questionnaire, the user questionnaire having a section for free-form comments.

9. A computer-implemented method, comprising:

gathering user information from at least one source;

creating at least one semantic abstract corresponding to the user information;

identifying emotion-related information within the at least one semantic abstract; and

creating at least one actionable item based at least in part on the at least one semantic abstract and the identified emotion-related information.

10. The computer-implemented method of claim 9, wherein the at least one source comprises at least one of a user document and a user event.

11. The computer-implemented method of claim 9, wherein the at least one source comprises at least one of private content, world content, and restricted content.

12. The computer-implemented method of claim 9, further comprising automatically executing the at least one actionable item.

13. The computer-implemented method of claim 9, further comprising classifying the emotion-related information.

14. The computer-implemented method of claim 13, further comprising assigning an emotion intensity value to the emotion-related information.

15. The computer-implemented method of claim 14, wherein the at least one actionable item is based at least in part on the emotion intensity value of the emotion-related information.

16. A system, comprising:

a gathering module to gather group information pertaining to a group of users;

a semantic module to create a semantic abstract based at least in part on the group information;

an emotion detection module to detect at least one emotion-related item within the semantic abstract; and

an analysis module to generate an output based at least in part on a correlation of at least two of the user information, the semantic abstract, and the at least one emotion-related item.

17. The system of claim 16, further comprising a predictive service module to implement the output from the analysis module.

18. The system of claim 16, wherein the predictive service module implements the output by providing the user with a recommendation.

19. The system of claim 18, wherein the predictive service module implements the output by updating the recommendation based on a newly detected emotion-related item.

20. The system of claim 16, further comprising an emotion intensity measurement module operable to measure an emotion intensity level of the at least one emotion-related item.

21. The system of claim 20, wherein the generated output is further based on the emotion intensity level.