AUTOMATICALLY MINING INTENTS OF A GROUP OF QUERIES

• US 20110208715A1
• Filed: 02/23/2010
• Published: 08/25/2011
• Est. Priority Date: 02/23/2010
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Chen, Zheng, Wang, Gang, Ni, Xiaochuan, Sun, Jian-Tao
• Application Number:
  US12/710,973
• Publication Number:
  US 20110208715A1
• Time in Patent Office: Days
• US Class Current: 707/709
• CPC Class Codes: G06F 16/332 Query formulation
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9536 Search customisation based on social or collaborative filtering

Abstract

The automatic search intent mining technique described herein pertains to a technique for mining search intent from a group of queries. The automatic search intent mining technique described herein automatically mines search intents from a group of queries. The technique leverages knowledge of query log data in order to determine search intent. The automatic search intent mining technique, in one embodiment, utilizes three kinds of information sources: Web page content, Web page structure and search engine query log data to mine intents for a group of queries. In one embodiment of the technique, the three data sources are used separately to mine candidate search intents for each of the three sources. The candidate search intents extracted from each of the three sources are then integrated to form the final search intents.

Claims

1. A computer-implemented process for automatically mining search intent for a group of search queries, comprising:

using a computing device for;

inputting a group of search queries;

mining a first set of search intent candidates for the group of search queries by using Web page content of Web pages returned in response to the group of search queries;

mining a second set of search intent candidates for the group of queries by using Web page structures of Web pages returned in response to the group of search queries;

mining a third set of search intent candidates for the group of queries by using search query log data;

integrating the first, second and third set of search intent candidates; and

extracting the common search intent candidates from the integrated first, second and third set of search intent candidates as the final search intents of the group of search queries.

2. The computer-implemented process of claim 1, wherein mining the first set of search intent candidates further comprises:

searching each query in the group of search queries and collecting corresponding search content for each query;

extracting key phrases from the search content corresponding to each query in the group of search queries;

integrating the key phrases from the search content of all the search queries; and

extracting common key phrases from the integrated key phrases as the first set of search intent candidates.

3. The computer-implemented process of claim 1, wherein mining the second set of search intent candidates further comprises:

searching each query in the group of search queries and collecting corresponding search result pages for each query;

extracting navigation bars from each Web page of the corresponding search result pages by using HTML structure information;

integrating the key phrases from the navigation bars extracted from the Web pages of all the search queries; and

extracting common key phrases as the second set of search intent candidates.

4. The computer-implemented process of claim 3 wherein extracting navigation bars using the HTML structure information further comprises analyzing a Document Object Model (DOM) tree of each Web page of the corresponding search results.

5. The computer-implemented process of claim 1, wherein mining the third set of search intent candidates further comprises:

extracting related queries and sub-queries for each query in the group of search queries by using click through information in a search query log that generated each query in the group of queries;

integrating the related queries, sub-queries and each query in the group of search queries;

extracting common key phrases from the integrated related queries, sub-queries and queries as the third set of search intent candidates.

6. The computer-implemented process of claim 1, wherein extracting the common search intent candidates from the integrated first, second and third set of search intent candidates as the final search intents of the group of search queries, further comprises extracting the common key phrases from the integrated search intent candidates of the first, second and third search intent candidates as the final search intents of the group of queries.

7. The computer-implemented process of claim 6, wherein the common search intent candidates of the first, second and third search intent candidates are extracted as the final search intents of the group of queries based on the frequency of the common key phrases.

8. The computer-implemented process of claim 6, wherein the common search intent candidates of the first, second and third search intent candidates are weighted in extracting the final search intents of the group of queries.

9. A computer-implemented process for automatically mining search intent from a group of search queries, comprising:

using a computing device for;

inputting a grouping of queries and associated search query log data;

separately mining search intent candidates from at least one of search result content, search result structure and search result usage data;

integrating the search intent candidate candidates separately mined from the search result content, search result structure and search result usage data; and

extracting the most common search intent candidates from the integrated search intent candidates as the final search intents for the group of search queries.

10. The computer-implemented process of claim 9, wherein the search query log data further comprises a sequence of search actions, one per user query, each comprising:

terms that compose a query,

documents returned by the a engine,

links in the documents have been followed by a user,

a rank of the documents in the list of search results,

a date and time each search action or link activation took place,

and an anonymous identifier for each session.

11. The computer-implemented process of claim 9, wherein search result content further comprises content of Web page data.

12. The computer-implemented process of claim 9, wherein the search result content further comprises search engine snippets.

13. The computer-implemented process of claim 9, wherein the search result structure data further comprises Web page structure data.

14. The computer-implemented process of claim 9, wherein the search result structure data is determining by using a DOM tree of a Web page.

15. A system for automatically determining a user'"'"'s search intent, comprising:

a general purpose computing device;

a computer program comprising program modules executable by the general purpose computing device, wherein the computing device is directed by the program modules of the computer program to,

mining search intent candidates for a group of search queries by using search result content data, search result usage data and search result structure data;

integrating the search intent candidates obtained by mining the search result content data, search result usage data and search result structure data of the group of search queries; and

extracting a set of final search intents by extracting common search intent candidates from the integrated search intent candidates.

16. The system of claim 15, further comprising a module for assigning different weights to different types of search intent candidates obtained by mining the search result content data, search result usage data and search result structure data of the group of search queries.

17. The system of claim 15, further comprising a module for using the final search intents to determine what type of information was searched for over a given time period.

18. The system of claim 15, further comprising a module for using the final search intents to generate key search words to embed in one or more files to be searched.

19. The system of claim 15, further comprising a module for using the final search intents to improve the relevance of subsequent search results returned in response to a new query.

20. The system of claim 15, wherein search result structure data is obtained by using navigational click through data of a user navigating hyperlinks on Web pages returned in search results.