Automatic Identification of Related Search Keywords

• US 20130006958A1
• Filed: 09/10/2012
• Published: 01/03/2013
• Est. Priority Date: 10/31/2005
• Status: Active Grant

• Current Assignee: RPX Corporation
• Original Assignee: Lycos Incorporated (Brightcom Group Ltd.)
• Inventors: Cava, William
• Granted Patent: US 9,015,176 B2
• Time in Patent Office: Days
• US Class Current: 707/711
• CPC Class Codes: G06F 16/3322 using system suggestions G06F16/3325 takes precedence
• CPC Class Codes: G06F 16/3338 Query expansion
• 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 16/9538 Presentation of query results
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06F 40/205 Parsing

Abstract

Keyword expansion is used to expand a particular keyword into multiple related keyword candidates using a collection of data that relates to search queries performed using one or more search engines. The data identifies search terms from associated search queries. A particular keyword is identified and one or more candidate keywords related to the particular keyword are identified based on the data.

Claims

1. A computer-implemented method for identifying keyword candidates, the method comprising:

collecting data relating to search queries performed using at least one search engine, the data identifying search terms from associated search queries;

identifying a particular keyword; and

identifying at least one candidate keyword related to the particular keyword based on the data.

2. The method of claim 1 further comprising determining associated search queries by identifying search queries performed within a search session.

3. The method of claim 2 further comprising identifying a set of search queries based on each of the search queries in the set being received from a particular location, wherein the search session comprises the set of search queries.

4. The method of claim 3 wherein identifying the set of search queries is further based on each of the search queries in the set being performed within a predetermined time.

5. The method of claim 3 further comprising determining the particular location based on an originating address associated with each of the search queries in the set.

6. The method of claim 3 further comprising determining the particular location based on data stored on a device from which each search query originates.

7. The method of claim 1 further comprising determining associated search queries by identifying search queries with related elements.

8. The method of claim 1 wherein the at least one candidate keyword comprises a search term included in a search query associated with at least one search query that includes the particular keyword.

9. The method of claim 1 wherein identifying the at least one candidate keyword comprises at least one of identifying different stems of a base term or identifying possible misspellings of a term.

10. The method of claim 1 wherein identifying the at least one candidate keyword comprises analyzing the data for patterns of similar search tendencies.

11. The method of claim 1 further comprising rating candidate keywords based on at least one of an identification of search term usage trends or a cost associated with each candidate keyword.

12. An article comprising at least one machine-readable medium storing instructions for causing data processing apparatus to perform operations to:

aggregate data identifying associations between different search terms based on received search queries;

receive an identification of a particular keyword;

identify at least one candidate keyword related to the particular keyword based on the aggregated data.

13. The article of claim 12 wherein the at least one machine-readable medium stores instructions for causing data processing apparatus to further perform operations comprising collecting information relating to usage trends among the different search terms, and wherein identifying at least one candidate keyword comprises using the information relating to usage trends.

14. The article of claim 12 wherein the at least one machine-readable medium stores instructions for causing data processing apparatus to further perform operations comprising weighting the at least one candidate keyword based on a cost relating to associating each candidate keyword with predetermined information.

15. The article of claim 12 wherein associations between different search terms are identified based on search terms included in associated search queries.

16. The article of claim 15 wherein different search queries are identified as associated search queries based on at least one factor selected from the group consisting of the different search queries being included in a search session, the different search queries being received from a particular location, the different search queries being received within a particular time, and the different search queries including search terms having a predetermined association.

17. A computer-implemented method for identifying keyword candidates, the method comprising:

identifying a particular keyword;

generating a set of related keywords relating to the particular keyword;

rating the related keywords based at least in part on a determination of a relative value associated with each related keyword.

18. The method of claim 17 wherein the relative value is based on usage trends for the related keyword in search queries.

19. The method of claim 17 wherein the relative value is based on a cost associated with the related keyword.

20. The method of claim 19 the cost comprises a cost relating to associating advertising with the related keyword.