Search engine for a computer network

• US 8,078,602 B2
• Filed: 12/17/2004
• Issued: 12/13/2011
• Est. Priority Date: 12/17/2004
• Status: Active Grant

• Current Assignee: Gula Consulting Limited Liability Company (Intellectual Ventures LLC)
• Original Assignee: Claria Innovations LLC
• Inventors: Martin, Anthony G.
• Primary Examiner(s): Fleurantin, Jean B
• Application Number:
  US11/015,583
• Publication Number:
  US 20060136378A1
• Time in Patent Office: 2,552 Days
• Field of Search: 707 1- 10, 707100-1041, 707200-206
• US Class Current: 707/706
• 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

Abstract

In one embodiment, client-side programs are employed to observe the navigation of consumers to various websites. Addresses of web pages viewed by consumers may be used to fetch the web pages. A fetched web page may be parsed for one or more keywords. The relevance of the web page to a keyword may be ranked according to consumer preferences, which may relate to consumer interaction with the web page. Web pages and their ranking information may be stored in an index. The index may be consulted to find links to web pages relevant to a keyword employed in a search request.

Claims

1. A method for presenting results in response to a search query, the method comprising the steps of:

(A) obtaining consumer navigation data and behavioral data from multiple user computers;

(B) for each of a plurality of web pages identified by said navigation data, using said consumer navigation data and said behavioral data to determine corresponding implied consumer preference data;

(C) building a search engine index using at least the consumer navigation data and the implied consumer preference data, said step of building comprising;

(c1) using said consumer navigation data to determine a particular web page viewed on at least one of said multiple user computers;

(c2) parsing a copy of the particular web page to determine the occurrence of one or more keywords in the particular web page; and

(c3) ranking the particular web page relative to at least some of the one or more keywords, said ranking being based at least in part on results of the parsing and on implied consumer preference data associated with the particular web page;

(D) receiving a search request based on a search keyword; and

(E) in response to said search request, retrieving results from the search engine index, said results identifying a plurality of web pages, and

(F) providing the results ordered, at least in part, by a ranking of each of the plurality of web pages relative to the search keyword.

2. The method of claim 1, wherein the consumer navigation data include addresses of web pages viewed at one or more user computers.

3. The method of claim 1, wherein the implied consumer preference data for a particular web page include an amount of time one or more users spent viewing the particular web page.

4. The method of claim 1, wherein the implied consumer preference data for a particular web page include actions taken while viewing the particular web page.

5. The method of claim 1 further comprising:

repeating steps (c1) to (c3) for multiple web pages identified in the consumer navigation data.

6. The method of claim 1 wherein at least some of the consumer navigation data and the behavioral data are obtained from multiple computer programs running on said multiple user computers.

7. The method of claim 6 wherein at least some of the multiple computer programs are browser independent.

8. The method of claim 1 wherein at least some of the consumer navigation data and the behavioral data are obtained from multiple computer programs running independently of browser programs on said multiple user computers.

9. A server comprising:

data storage configured to receive consumer navigation data and behavioral data from multiple user computers; and

a search engine indexer configured to;

determine, for each of a plurality of web pages identified in said consumer navigation data, corresponding implied consumer preference data, said implied consumer preference data being based, at least in part, on said consumer navigation data and said behavioral data; and

to

build a search engine index using the consumer navigation and the implied consumer preference data, by;

(c1) using said consumer navigation data to determine a particular web page viewed by at least one of said multiple user computers;

(c2) parsing a copy of the particular web page to determine the occurrence of one or more keywords in the particular web page; and

(c3) ranking the particular web page relative to at least some of the one or more keywords, said ranking being based at least in part on results of the parsing and on implied consumer preference data associated with the particular web page;

the search engine being further configured to receive a search request based on a search keyword, and, responsive to said search request,

to retrieve results from the search engine index, said results identifying a plurality of web pages corresponding to said search keyword, and

to provide said results, ordered, at least in part, by a ranking of each of the plurality of web pages relative to the search keyword.

10. The system of claim 9, wherein the consumer navigation data include addresses of web pages viewed at a user computer.

11. The system of claim 9, wherein the implied consumer preference data for a particular web page include an amount of time users spent viewing the particular web page.

12. The system of claim 9, wherein the implied consumer preference data for a particular web page include actions taken while viewing the particular web page.

13. The server of claim 9 wherein at least some of the consumer navigation data and the behavioral data are obtained from multiple computer programs running on said multiple user computers.

14. The server of claim 13 wherein at least some of the multiple computer programs are browser independent.

15. The server of claim 9 wherein at least some of the consumer navigation data and the behavioral data are obtained from multiple computer programs running independently of browser programs on said multiple user computers

16. A computer-readable storage medium comprising computer-readable program code, the computer-readable storage code being executable by a processor to perform a method, the method comprising:

(A) obtaining consumer navigation data and behavioral data from multiple user computers;

(B) for each of a plurality of web pages identified by the consumer navigation data, using said consumer navigation data and said behavioral data to determine implied consumer preference data;

(C) building a search engine index using at least the consumer navigation and the implied consumer preference data, wherein said step of building comprises;

(c1) using said consumer navigation data to determine a particular web page viewed by at least one of said multiple user computers;

(c2) parsing a copy of the particular web page to determine the occurrence of one or more keywords in the particular web page; and

(c3) ranking the particular web page relative to at least some of the one or more keywords, said ranking being based at least in part on results of the parsing and on implied consumer preference data associated with the particular web page;

(D) receiving a search request based on a search keyword; and

(E) based on the search request, retrieving results from the search engine index, said results identifying a plurality of web pages, and

(F) providing the results, ordered, at least in part, by a ranking of each of the plurality of web pages relative to the search keyword.

17. The computer-readable storage medium of claim 16, wherein the consumer navigation data include addresses of web pages viewed at a user computer.

18. The computer-readable storage medium of claim 16, wherein the implied consumer preference data for a particular web page include an amount of time one or more users spent viewing the particular web page.

19. The computer-readable storage medium of claim 16, wherein the implied consumer preference data for a particular web page include actions taken while viewing the particular web page.

20. A method comprising the steps of:

(A) obtaining consumer navigation data from computer programs running on multiple user computers, said navigation data comprising data identifying a plurality of web pages viewed at said user computers;

(B) obtaining behavioral data from said multiple user computers, said behavioral data relating to said plurality of web pages identified by said consumer navigation data;

(C) for each of the plurality of web pages identified by the navigation data, using said navigation data and said behavioral data to determine corresponding implied consumer preference data;

(D) building a search engine index using at least the consumer navigation data and the implied consumer preference data, said step of building comprising, for each particular web page of the plurality of web pages identified by the navigation data;

(d1) parsing a copy of the particular web page to determine the occurrence of one or more keywords in the particular web page; and

(d2) ranking the particular web page relative to at least some of the one or more keywords, said ranking being based at least in part on results of the parsing and on implied consumer preference data associated with the particular web page; and

(E) in response to a search request based on a search keyword, retrieving results from the search engine index, said results identifying a plurality of web pages, and

(F) providing the results ordered, at least in part, by a ranking of the plurality of web pages relative to the search keyword.

21. The method of claim 20 wherein at least some of the multiple computer programs are browser independent.

22. The system of claim 20, wherein the consumer navigation data include addresses of web pages viewed at a user computer.

23. The system of claim 20, wherein the implied consumer preference data for a particular web page include an amount of time users spent viewing the particular web page.

24. The system of claim 20, wherein the implied consumer preference data for a particular web page include actions taken while viewing the particular web page.

26. The method of claim 20 wherein at least some of the multiple computer programs running on the multiple user computers are running independently of browser programs on said multiple user computers.

25. A method comprising the steps of:

(A) obtaining consumer navigation data from browser-independent computer programs running on multiple user computers, said navigation data comprising data identifying a plurality of web pages viewed at said user computers;

(B) for each specific web page of the plurality of web pages identified by the navigation data, using said navigation data to determine corresponding implied consumer preference data for that specific web page;

(C) for each particular web page of the plurality of web pages identified by the navigation data;

(c1) parsing the copy of the particular web page to determine the occurrence of one or more keywords in the particular web page;

(c2) ranking a particular web page relative to at least some of the one or more keywords, said ranking being based at least in part on results of the parsing and on implied consumer preference data associated with the particular web page;

(c3) storing results of said ranking in a search engine index; and

,

(D) in response to a search request based on a search keyword, retrieving results from the search engine index, said results identifying a plurality of web pages, and

(E) providing the results ordered, at least in part, by a ranking of the plurality of web pages relative to the search keyword.

27. The system of claim 25, wherein the consumer navigation data include addresses of web pages viewed at a user computer.

28. The system of claim 25, wherein the implied consumer preference data for a particular web page include one or more of:

(i) an amount of time users spent viewing the particular web page; and

(ii) actions taken while viewing the particular web page.