PERSONALIZED SEARCH LIBRARY BASED ON CONTINUAL CONCEPT CORRELATION

• US 20140172828A1
• Filed: 12/19/2012
• Published: 06/19/2014
• Est. Priority Date: 12/19/2012
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Mo, Stanley, Wouhaybi, Rita H., Mian, Mubashir A., Kohlenberg, Tobias M., Baca, Jim S.
• Granted Patent: US 9,582,572 B2
• Time in Patent Office: Days
• US Class Current: 707/722
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 2216/01 Automatic library building

Abstract

A system, devices, and methods for providing a personalized search library based on continual concept correlation include a client computing device and a personalized content server. Content events representing content accessed or manipulated by a user of the client computing device are continually generated. Content associated with the content events is continually parsed and analyzed to extract main concepts. The extracted concepts are correlated and weighted into a concept model, based on the order of the content events. The concept model parallels the structure of the user'"'"'s memory. Data sources are continually searched for content relevant to a current context of the concept model. Relevant content is indexed according to the concept model. The relevant content may be made available to the user upon request or proactively. Relevant content may be cached for future use by the user. Other embodiments are described and claimed.

Claims

1. A computing device to provide a personalized search library based on continual concept correlation, the computing device comprising:

a natural language analyzer to (i) receive event data representing content accessed by a user of a client computing device and (ii) analyze the event data to extract concepts of the content; and

a correlation module to (i) correlate the extracted concepts based on an order of the event data, (ii) adjust a weight of each extracted concept based on a frequency of the extracted concept occurring in the content, and (iii) store the correlated and weighted extracted concepts in a concept model that identifies the relative correlation and weights between each extracted concept.

2. The computing device of claim 1, further comprising:

a search module to search one or more content sources for relevant search results based on a current context of the concept model; and

a personalized content module to (i) index the search results in the personalized search library according to the concept model and (ii) facilitate access to the personalized search library by the user.

3. The computing device of claim 2, wherein the personalized content module comprises a personalized content module to provide content from the personalized search library to the user in response to a search query from the user.

4. The computing device of claim 2, wherein the personalized content module comprises a personalized content module to (i) retrieve content indexed by the personalized search library and (ii) store the retrieved content in a content cache of the computing device.

5. The computing device of claim 2, wherein the personalized content module comprises a personalized content module to (i) retrieve content indexed by the personalized search library and (ii) provide the content to the user.

6. The computing device of claim 2, wherein the computing device is a personalized content server.

7. The computing device of claim 2, wherein the computing device is the client computing device.

8. One or more non-transitory, machine readable media comprising a plurality of instructions that in response to being executed result in a computing device:

receiving event data representing content accessed by a user of a client computing device;

analyzing the event data to extract concepts of the content;

correlating the extracted concepts based on an order of the event data;

adjusting a weight of each extracted concept based on a frequency of the extracted concept occurring in the content; and

storing the correlated and weighted extracted concepts in a concept model that identifies the relative correlation and weights between each extracted concept.

9. The machine readable media of claim 8, further comprising a plurality of instructions that in response to being executed result in the computing device:

searching one or more content sources for relevant search results based on a current context of the concept model;

indexing the search results in the personalized search library according to the concept model; and

facilitating access to the personalized search library by the user.

10. The machine readable media of claim 9, wherein allowing the user to access the personalized search library comprises providing content from the personalized search library to the user in response to a search query from the user.

11. The machine readable media of claim 9, wherein allowing the user to access the personalized search library comprises:

retrieving content indexed by the personalized search library; and

storing the retrieved content in a content cache of the computing device.

12. The machine readable media of claim 9, wherein allowing the user to access the personalized search library comprises:

retrieving content indexed by the personalized search library; and

providing the content to the user.

13. The machine readable media of claim 9, wherein the computing device is a personalized content server.

14. The machine readable media of claim 9, wherein the computing device is the client computing device.

15. A method to provide a personalized search library based on continual concept correlation, the method comprising:

receiving event data representing content accessed by a user of a client computing device;

analyzing the event data to extract concepts of the content;

correlating the extracted concepts based on an order of the event data;

adjusting a weight of each extracted concept based on a frequency of the extracted concept occurring in the content; and

storing the correlated and weighted extracted concepts in a concept model that identifies the relative correlation and weights between each extracted concept.

16. The method of claim 15, further comprising:

searching one or more content sources for relevant search results based on a current context of the concept model;

indexing the search results in the personalized search library according to the concept model; and

facilitating access to the personalized search library by the user.

17. The method of claim 16, wherein allowing the user to access the personalized search library comprises providing content from the personalized search library to the user in response to a search query from the user.

18. The method of claim 16, wherein allowing the user to access the personalized search library comprises:

retrieving content indexed by the personalized search library; and

storing the retrieved content in a content cache of the computing device.

19. The method of claim 16, wherein:

receiving the event data comprises receiving the event data on a personalized content server;

analyzing the event data comprises analyzing the event data on the personalized content server;

correlating the extracted concepts comprises correlating the extracted concepts on the personalized content server;

adjusting the weight of the extracted concepts comprises adjusting the weight of the extracted concepts on the personalized content server;

storing the correlated and weighted concepts comprises storing the correlated and weighted concepts on the personalized content server;

searching the one or more content sources comprises searching the one or more content sources using the personalized content server; and

indexing the personal content collection comprises indexing the personal content collection on the personalized content server.

20. The method of claim 16, wherein:

receiving the event data comprises receiving the event data on the client computing device;

analyzing the event data comprises analyzing the event data on the client computing device;

correlating the extracted concepts comprises correlating the extracted concepts on the client computing device;

adjusting the weight of the extracted concepts comprises adjusting the weight of the extracted concepts on the client computing device;

storing the correlated and weighted concepts comprises storing the correlated and weighted concepts on the client computing device;

searching the one or more content sources comprises searching the one or more content sources using the client computing device;

indexing the personal content collection comprises indexing the personal content collection on the client computing device; and

allowing the user to access the personalized search library comprises allowing the user to access the personalized search library on the client computing device.