PREDICTIVE SERVICE SYSTEMS

• US 20100122312A1
• Filed: 11/07/2008
• Published: 05/13/2010
• Est. Priority Date: 11/07/2008
• Status: Abandoned Application

• Current Assignee: Novell Intellectual Property Holdings, Inc.
• Original Assignee: Novell Incorporated (Open Text Corporation)
• Inventors: Bultmeyer, Jon, Carter, Stephen R., Isaacson, Scott Alan, Green, Tammy
• Application Number:
  US12/267,279
• Publication Number:
  US 20100122312A1
• Time in Patent Office: Days
• US Class Current: 726/1
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

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, a policy service to enforce a policy, and a predictive service to act on an actionable item that is created based on the user information, the semantic abstract, and the policy. The system can also include an analysis module to create the actionable item and send it to the predictive service. The system can also include an identity service to create a crafted identity for the user.

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 policy service operable to enforce at least one policy; 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 at least one policy.

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, 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, further comprising at least one identity service operable to create a crafted identity for the user, wherein the at least one actionable item is based at least in part on the crafted identity.

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

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

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

7. The predictive service system of claim 6, wherein the information pertaining to the collaboration group comprises at least one of a collaboration document and a collaboration event.

8. The predictive service system of claim 6, wherein the information pertaining to the collaboration group comprises information pertaining to a collaboration content flow.

9. 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.

10. The predictive service system of claim 1, wherein the at least one actionable item comprises a creation of an RSS feed.

11. The predictive service system of claim 1, wherein the at least one actionable item comprises a creation of a travel itinerary.

12. The predictive service system of claim 1, wherein the at least one actionable item comprises at least one modification to an existing travel itinerary.

13. The predictive service system of claim 1, wherein the user information comprises at least one parametric user preference.

14. The predictive service system of claim 13, wherein the at least one actionable item is based at least in part on the at least one parametric user preference.

15. A computer-implemented method, comprising:

gathering user information from at least one source;

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

correlating the at least one semantic abstract with at least one of a user identity and a policy; and

creating at least one actionable item based at least in part on the correlating.

16. The computer-implemented method of claim 15, wherein the at least one source comprises at least one of a user document and a user event.

17. The computer-implemented method of claim 15, wherein the at least one source comprises at least one of a collaboration document and a collaboration event.

18. The computer-implemented method of claim 15, wherein the at least one source comprises at least one of private content, world content, and restricted content.

19. The computer-implemented method of claim 15, further comprising automatically executing the at least one actionable item.

20. The computer-implemented method of claim 15, further comprising prompting the user for direction regarding execution of the at least one actionable item.

21. The computer-implemented method of claim 15, wherein creating the at least one actionable item comprises creating a new calendar event in a user calendar application.

22. The computer-implemented method of claim 15, wherein creating the at least one actionable item comprises modifying an existing calendar event in a user calendar application.

23. The computer-implemented method of claim 15, wherein the user information comprises at least one user preference.

24. The computer-implemented method of claim 15, wherein the at least one actionable item is based at least in part on a prediction confidence level.

25. The computer-implemented method of claim 15, further comprising narrowing the at least one actionable item based at least in part on at least one parametric user preference.

26. The computer-implemented method of claim 25, wherein the at least one parametric user preference corresponds to a positive user preference.

27. The computer-implemented method of claim 25, wherein the at least one parametric user preference corresponds to a negative user preference.

28. A system, comprising:

an identity module to manage an identity for a user;

a policy module to manage a policy;

a gathering module to gather user information;

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

an analysis module to generate an output based at least in part on a correlation of at least two of the identity, the policy, the user information, and the semantic abstract.

29. The system of claim 28, further comprising a predictive service module to implement the output from the analysis module.

30. The system of claim 28, wherein the predictive service module implements the output by providing the user with a recommendation.

31. The system of claim 28, further comprising an external agent to modify the user information.