Keyword recommendation for internet search engines

• US 20050198068A1
• Filed: 03/04/2004
• Published: 09/08/2005
• Est. Priority Date: 03/04/2004
• Status: Active Grant

• Current Assignee: Twitter Inc (X Holdings Corp.)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Bhayani, Jayesh Vrajlal, Chand, Jagdish, Mukherjee, Shouvick, Raj, Ravi Narasimhan
• Granted Patent: US 8,676,830 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9532 Query formulation

Abstract

A computer implemented method of generating keyword recommendations is provided, which includes providing keyword frequency data in computer readable media that indicate frequency counts of keywords used in past internet searches; providing keyword affinity data in computer readable media that indicate affinities between pairs of keywords used in past user internet searches; identifying keywords from the keyword frequency data that include the selected keyword; identifying keywords from the keyword affinity data that have an affinity to the selected keyword; and prioritizing the identified keywords based upon the keyword frequency.

Claims

1. A computer implemented method of generating keyword recommendations comprising:

providing keyword frequency data in computer readable media that indicate frequency counts of keywords used in past internet searches;

providing keyword affinity data in computer readable media that indicate affinities between pairs of keywords used in past user internet searches;

identifying keywords from the keyword frequency data that include the selected keyword;

identifying keywords from the keyword affinity data that have an affinity to the selected keyword; and

prioritizing the identified keywords based upon the keyword frequency.

2. The method of claim 1,

wherein identifying keywords from the keyword frequency data that include the selected keyword includes searching the keyword frequency data for keywords that include the selected keyword;

and

wherein identifying keywords from the keyword affinity data that have an affinity to the selected keyword includes searching the keyword affinity data for keywords that include the selected keyword.

3. The method of claim 1,

wherein identifying keywords from the keyword frequency data include the selected keyword includes producing a first table that includes a list of keywords that include the selected keyword;

and

wherein identifying keywords from the keyword affinity data that have an affinity to the selected keyword includes producing a second table that includes a list of keywords that have an affinity with the selected keyword.

4. The method of claim 1,

wherein identifying keywords from the keyword frequency data that include the selected keyword includes producing a first table that includes a list of keywords that include the selected keyword;

wherein identifying keywords from the keyword affinity data that have an affinity to the selected keyword includes producing a second table that includes a list of keywords that have an affinity with the selected keyword;

wherein prioritizing the identified keywords includes associating frequency counts from the frequency data with keywords in the first table; and

wherein prioritizing the identified keywords includes associating frequency counts from the frequency data with keywords in the second table.

5. The method of claim 1,

wherein prioritizing the identified keywords includes ordering the keywords identified from the keyword frequency data according to the frequency counts indicted by the frequency data;

and

wherein prioritizing the identified keywords includes ordering the keywords identified from the keyword affinity data as having an affinity to the selected keyword according to the frequency counts indicted by the frequency data.

6. The method of claim 1,

wherein prioritizing the identified keywords includes producing a data structure in which identified keywords from the frequency data and from the affinity data are ordered according to the frequency counts indicted by the frequency data.

7. The method of claim 1,

wherein identifying keywords from the keyword frequency data include the selected keyword includes producing a first list that includes a list of keywords that include the selected keyword;

wherein identifying keywords from the keyword affinity data that have an affinity to the selected keyword includes producing a second list that includes a list of keywords that have an affinity with the selected keyword; and

wherein prioritizing identified keywords includes producing a third list in which identified keywords from the first list and from the second list are merged together and ordered according to the frequency counts indicted by the frequency data.

8. The method of claim 1,

receiving a user-provided search request that includes the selected keyword;

and

providing the prioritized identified keywords to the user who provided the search request.

9. The method of claim 1,

wherein prioritizing the identified keywords includes producing a table in which identified keywords from the frequency data and from the affinity data are merged together and ordered according to the frequency counts indicted by the frequency data;

and

further including the steps of;

receiving a user-provided search request that includes the selected keyword; and

providing the identified keywords, as ordered in the table, to the user who provided the search request.

10. The method of claim 1,

wherein receiving a user-provided search request involves receiving a request communicated by the user over the internet;

and

wherein providing the identified keywords involves communicating the request to the user over the internet.

11. A computer implemented method of generating keyword recommendations comprising:

receiving a user-provided search request that includes a user indicated keyword;

providing keyword frequency data that indicate frequency counts of keywords used in past internet searches;

providing keyword affinity data that indicate affinities between pairs of keywords used in past user internet searches;

searching the keyword frequency data to identify keywords from that include the user indicated keyword;

searching the keyword affinity data to identify keywords that have an affinity to the user indicated keyword; and

producing a data structure in which identified keywords from the frequency data and from the affinity data are ordered according to frequency counts indicted by the frequency data; and

providing the ordered identified keywords to the user.

12. An article of manufacture including computer readable medium encoded with computer readable code comprising:

keyword frequency data that indicate frequency counts of keywords used in past internet searches;

keyword affinity data that indicate affinities between pairs of keywords used in past user internet searches;

computer code means for using a selected keyword to identify keywords from the keyword frequency data that include the selected keyword;

computer code means for using the selected keyword to identify keywords from the keyword affinity data that have an affinity to the selected keyword; and

computer code means for using the keyword frequency data to prioritize the identified keywords.

13. The article of manufacture of claim 12 further including:

computer code means for receiving a user-provided search request that includes the user selected keyword; and

computer code means for providing the ordered identified keywords to the user.

14. An article of manufacture including computer readable medium encoded with computer readable code comprising:

keyword frequency data media that indicate frequency counts of keywords used in past internet searches;

keyword affinity data that indicate affinities between pairs of keywords used in past user internet searches;

computer code means for searching the keyword frequency data to identify keywords that include a selected keyword and for producing a first list that includes a list of keywords that include a selected keyword;

computer code means for searching the keyword affinity data to identify keywords that have an affinity to the selected keyword and for producing a second list that includes a list of keywords that have an affinity with the selected keyword; and

computer code means for producing a third list in which identified keywords from the first list and from the second list are merged together and ordered according to the frequency counts indicted by the frequency data.

15. The article of manufacture of claim 14 further including:

computer code means for receiving a user-provided search request that includes the user selected keyword; and

computer code means for providing the ordered identified keywords to the user.

16. A computer implemented internet search method comprising:

receiving a user-provided search request that includes a user indicated keyword;

providing keyword frequency data in computer readable media that indicate frequency counts of keywords used in past internet searches;

providing keyword affinity data in computer readable media that indicate affinities between pairs of keywords used in past user internet searches;

searching the keyword frequency data to identify keywords from that include the user indicated keyword;

searching the keyword affinity data to identify keywords that have an affinity to the user indicated keyword; and

producing a data structure in which identified keywords from the frequency data and from the affinity data are ordered according to frequency counts indicted by the frequency data;

providing to the user a list of one or more web pages that satisfy the user-provided search request; and

providing to the user the ordered identified keywords.

17. A system for enhancing internet searches comprising:

a web server that retrieves one or more web pages in response to a user search request that includes a user-indicated keyword;

keyword frequency data in computer readable media that indicate frequency counts of keywords used in past internet searches;

keyword affinity data in computer readable media that indicate affinities between pairs of keywords used in past user internet searches;

a keyword recommendation server that is coupled to communicate with the web server and that,

searches the keyword frequency data to identify keywords from that include the user-indicated keyword,

searches the keyword affinity data to identify keywords that have an affinity to the user-indicated keyword, and

prioritizes the identified keywords from the frequency data and from the affinity data according to frequency counts indicted by the frequency data.

18. The system of claim 17,

wherein the server produces a first table that includes a list of keywords from the keyword frequency data that include the user-indicated keyword;

and

wherein the server produces a second table that includes a list of keywords from the affinity data that have an affinity with the selected keyword.

19. The system of claim 17,

wherein the server produces a list of identified keywords from the keyword frequency data that include the user-indicated keyword;

wherein the server produces a list of identified keywords from the affinity data that have an affinity with the selected keyword;

wherein the server prioritizes identified keywords from the keyword frequency data by associating frequency counts from the frequency data with keywords in the first list; and

wherein the server prioritizes identified keywords from the affinity data by associating frequency counts from the frequency data with keywords in the second list.

20. The system of claim 17,

wherein the server produces a list of identified keywords from the keyword frequency data that include the user-indicated keyword;

wherein the server produces a list of identified keywords from the affinity data that have an affinity with the selected keyword; and

wherein the server prioritizes identified keywords by producing a third list in which identified keywords from the frequency data and from the affinity data are merged together and ordered according to the frequency counts indicted by the frequency data.

21. The system of claim 17 further including:

an internet search engine coupled to communicate with the web server.