Recommendation system that identifies a valuable user action by mining data supplied by a plurality of users to find a correlation that suggests one or more actions for notification

• US 7,657,493 B2
• Filed: 12/20/2006
• Issued: 02/02/2010
• Est. Priority Date: 09/28/2006
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Glasgow, Dane A., Cheng, Lili, MacLaurin, Matthew B., Meijer, Henricus Johannes Maria, Ozzie, Raymond E., Flake, Gary W., Zaner-Godsey, Melora, Gates, William H. III, Larus, James R., Brumme, Christopher W., Blinn, Arnold N., Treadwell, David R. III, Gounares, Alexander G., Glasser, Daniel S., Mital, Amit, Bergstraesser, Thomas F., Snyder, Ira L. Jr., Mishra, Debi P., Dani, Nishant V., Connolly, Michael, Thekkath, Chandramohan A.
• Primary Examiner(s): Vincent; David R
• Assistant Examiner(s): Brown, Jr.; Nathan H
• Application Number:
  US11/613,930
• Publication Number:
  US 20080082467A1
• Time in Patent Office: 1,140 Days
• Field of Search: 706/12
• US Class Current: 706/12
• CPC Class Codes: G06F 16/27 Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06F 2216/03 Data mining

Abstract

Personal data mining mechanisms and methods are employed to identify relevant information that otherwise would likely remain undiscovered. Users supply personal data that can be analyzed in conjunction with data associated with a plurality of other users to provide useful information that can improve business operations and/or quality of life. Personal data can be mined alone or in conjunction with third party data to identify correlations amongst the data and associated users. Applications or services can interact with such data and present it to users in a myriad of manners, for instance as notifications of opportunities.

Claims

1. A recommendation system, comprising:

a memory and a processor;

an application component stored in the memory and executable on the processor that identifies at least one valuable user action based on at least one correlation determined from user data supplied by a plurality of users, the application component identifies individuals who are working on a similar project; and

a notification component stored in the memory and executable on the processor to generate a notification to at least one of the plurality of users that suggests the action, the notification component suggests the user consult with the individuals.

2. The system of claim 1, the notification component suggests actions that match user defined criteria.

3. The system of claim 1, the application component identifies a repetitive task and the notification component suggests the task be automated.

4. The system of claim 1, further comprising a data mining component stored in the memory and executable on the processor that identifies the at least one correlation from the user data.

5. The system of claim 4, the data mining component is a network service that interacts with remotely persisted user data.

6. The system of claim 4, further comprising a component stored in the memory and executable on the processor that extracts the user data from a device and provides the data to a remote network store accessible by the data mining component.

7. The system of claim 1, further comprising an ad component stored in the memory and executable on the processor that presents one or more advertisements to one of the plurality of users based on the personal data supplied by the user.

8. The system of claim 7, the one or more advertisements are provided in conjunction with the action suggested to a user.

9. The system of claim 1, further comprising a component stored in the memory and executable on the processor that facilitates sale of user information.

10. A personal recommendation method, comprising the following computer-implemented acts:

mining personal information supplied by a plurality of users to identify at least one correlation amongst the information;

suggesting one or more actions as a function of the at least one correlation; and

mining the personal information in accordance with a user defined algorithm.

11. The method of claim 10, further comprising filtering the one or more suggestions based on user defined criteria.

12. The method of claim 10, further comprising mining the personal information utilizing a third-party algorithm.

13. The method of claim 10, further comprising automatically capturing the personal information from one or more user devices.

14. The method of claim 10, further comprising supplying targeted advertisements to users in conjunction with the at least one correlation.

15. A personal recommendation method, comprising the following computer-implemented acts:

mining personal information supplied by a plurality of users to identify at least one correlation amongst the information;

suggesting one or more actions as a function of the at least one correlation;

providing at least a portion of the personal information to one or more advertisers; and

selling the information to the one or more advertisers and providing at least a portion of the revenue to a user.

16. The method of claim 15, further comprising filtering the one or more suggestions based on user defined criteria.

17. The method of claim 15, further comprising mining the personal information in accordance with a user defined algorithm.

18. The method of claim 15, further comprising mining the personal information utilizing a third-party algorithm.

19. The method of claim 15, further comprising automatically capturing the personal information from one or more user devices.

20. The method of claim 15, further comprising supplying targeted advertisements to users in conjunction with the at least one correlation.