PERSONAL DATA MINING

• US 20080082393A1
• Filed: 09/28/2006
• Published: 04/03/2008
• 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, Larus, James R., Brumme, Christopher W., Blinn, Arnold N., Gounares, Alexander G., Glasser, Daniel S., Snyder, Ira L., Mital, Amit, Bergstraesser, Thomas F., Mishra, Debi P., Dani, Nishant V., Connolly, Michael, Thekkath, Chandramohan A., Treadwell, David R., Gates, William H.
• Granted Patent: US 7,930,197 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• 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
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products

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 personal user information data mining system, comprising the following computer-implemented components:

a data mining component that identifies at least one correlation amongst personal user data supplied by a plurality of users; and

an application component that provides a user with the identified correlation.

2. The system of claim 1, the data mining component is a network service that interacts with remotely persisted user data.

3. The system of claim 2, the application component is distributed between a client device and network service.

4. The system of claim 2, further comprising a component that extracts the user data from a device and provides the data to a remote network store accessible by the data mining component.

5. The system of claim 1, further comprising a component that merges third party user data with the user supplied data.

6. The system of claim 1, further comprising a component that time stamps data to produce sequenced user data.

7. The system of claim 1, further comprising a component that normalizes user metadata to optimize identification of the at least one correlation.

8. The system of claim 1, further comprising a tag component that facilitates at least one of manual and automatic data tagging in accordance with a taxonomy.

9. The system of claim 1, further comprising a notification component that notifies a user of an opportunity based on the at least one correlation.

10. The system of claim 9, further comprising a context component that provides substantially real-time context data to the notification component to facilitate timely identification of an opportunity.

11. The system of claim 1, further comprising an ad component that presents advertisements to one of the plurality of users based on the personal data supplied by the user.

12. A method of mining user related information, comprising the following computer-implemented acts:

capturing personal information supplied by a plurality of users; and

identifying at least one correlation amongst the personal information.

13. The method of claim 12, further comprising time stamping the information to facilitate identification of time sensitive correlations.

14. The method of claim, 13, further comprising determining a valuable user action based on the at least one correlation.

15. The method of claim 14, further comprising notifying a user of the action when the value of the action is greater than cost of interruption.

16. The method of claim 12, further comprising:

merging third-party information pertaining to at one of the plurality of users with the personal information; and

determining at least one correlation based at least in part on the third-party information.

17. The method of claim 12, further comprising aggregating the information across users to preserve user privacy.

18. The method of claim 12, further comprising automatically tagging user data with metadata in accordance with a particular taxonomy.

19. The method of claim 12, further comprising supplying targeted advertisements to users in conjunction with the at least one correlation.

20. A computer implemented system for connecting users, comprising:

means for mining sequences of data associated with a plurality of individual users to identify correlations amongst the sequences; and

means for providing a notification to at least one user based on the identified correlations.