METHOD AND APPARATUS FOR DETERMINING THE SIGNIFICANCE AND RELEVANCE OF A WEB PAGE, OR A PORTION THEREOF

• US 20080005101A1
• Filed: 06/21/2007
• Published: 01/03/2008
• Est. Priority Date: 06/23/2006
• Status: Active Grant

• Current Assignee: Rohit Chandra
• Original Assignee: Rohit Chandra
• Inventors: Chandra, Rohit
• Granted Patent: US 8,661,031 B2
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

A method for determining the significance of a web page, or a portion thereof, is disclosed. Accordingly, a search engine or some other application analyzes user-generated highlights (as well as user-provided comments associated with the highlights) of a document to determine a document relevance score (e.g., Highlight Rank) for the document containing the user-generated highlights. The particular algorithm for determining the document relevance score will vary depending upon the particular implementation, but may generally be based upon an analysis of the number and quality of user-generated highlights and associated comments within a document. Based on this analysis, the search engine assigns the document a document relevance score, which is used for processing the document in accordance with instructions associated with a search query. For example, the document relevance score may be used in selecting and ordering documents returned in search results for a particular search query.

Claims

1. A computer-implemented method comprising:

assigning a document relevance score to a document based in part on an analysis of user-generated highlights associated with the document; and

processing the document, based in part on its document relevance score.

2. The computer-implemented method of claim 1, wherein the document relevance score is based in part on an analysis of user-initiated activities associated with the document.

3. The computer-implemented method of claim 1, wherein the document relevance score is based in part on an analysis of the number of users who have interacted with the document.

4. The computer implemented method of claim 1, wherein the document relevance score is based in part on a combination of one or more of the following components:

the number of highlights in the document, the number of comments associated with the document, the number of user-ratings associated with the document, the number of relevance flags associated with the document, the number of times the document has been viewed, the number of times the document has been emailed, the number of times the document has been marked as a user favorite, and/or the number of times the document has been copied.

5. The computer-implemented method of claim 1, wherein the document relevance score is based in part on a combination of one or more of the following components:

the number of users who have generated highlights on the document;

the number of users who have provided comments on the document, or a highlight associated with the document;

the number of users who have provided a rating for the document, or a highlight associated with the document, or a comment on the document;

the number of users who have flagged relevance;

the number of users who have viewed the document;

the number of users who have emailed the document;

the number of viewers who have marked the document as a favorite; and

/or the number of users who have copied the document.

6. The computer-implemented method of claim 1, wherein assigning a document relevance score to a document based in part on an analysis of user-generated highlights associated with the document includes determining a weighting factor for a highlight, comment, or other user action, made by a particular user, wherein the weighting factor is i) determined based on a rating associated with the particular user, and ii) used to weight the contribution of the highlight, comment, or other user action, to the document relevance score.

7. The computer-implemented method of claim 6, wherein the weighting factor associated with the particular user is determined based in part on the number of highlights or comments made by the particular user.

8. The computer-implemented method of claim 7, wherein the weighting factor associated with the particular user is determined based in part on ratings of the particular user that have been provided by other users.

9. The computer-implemented method of claim 7, wherein the weighting factor associated with the particular user is determined based on ratings of the particular user'"'"'s highlights, comments and/or other user actions, that have been provided by other users.

10. The computer-implemented method of claim 1, wherein processing the document based in part on its document relevance score includes processing a document in accordance with a search query so as to determine a document'"'"'s relevance and/or positioning in a listing of search results based on the document relevance score.

11. The computer-implemented method of claim 1, wherein processing the document based in part on its document relevance score includes displaying a graphic or icon with a link to the document in a list of search results, wherein the graphic or icon represents the document relevance score.

12. A computer-implemented method comprising:

providing search results to a search query, wherein said search results are selected and/or ordered based in part on an analysis of user-generated highlights associated with documents satisfying the search query.

13. The computer-implemented method of claim 12, further comprising:

determining a document relevance score for each of those documents satisfying the search query, wherein the document relevance score is based in part on the analysis of user-generated highlights.

14. The computer-implemented method of claim 13, wherein the document relevance score is based in part on an analysis of user-initiated activities associated with those documents satisfying the search query.

15. The computer-implemented method of claim 13, wherein the document relevance score is based in part on an analysis of the number of users who have interacted with those documents satisfying the search query.

16. The computer-implemented method of claim 12, wherein the document relevance score is based in part on a combination of one or more of the following components:

the number of highlights in a document, the number of comments associated with a document, the number of user-ratings associated with a document, the number of relevance flags associated with a document, the number of times a document has been viewed, the number of times a document has been emailed, the number of times a document has been marked as a user favorite, and/or the number of times a document has been copied.

17. The computer-implemented method of claim 12, wherein the document relevance score is based in part on a combination of one or more of the following components:

the number of users who have generated highlights on a document;

the number of users who have provided comments on a document, or a highlight associated with a document;

the number of users who have provided a rating for a document, or a highlight associated with a document, or a comment on a document;

the number of users who have flagged relevance;

the number of users who have viewed a document;

the number of users who have emailed a document;

the number of viewers who have marked a document as a favorite; and

/or the number of users who have copied a document.

18. The computer-implemented method of claim 12, wherein providing search results to a search query includes displaying a listing of links to documents satisfying the search query along with information representing the level of significance assigned to each document satisfying the search query.

19. The computer-implemented method of claim 12, wherein the search query specifies one or more search terms, and the documents satisfying the search query are those documents which contain the one or more keywords in a portion of the internet document associated with a user-generated highlight.

20. The computer-implemented method of claim 19, wherein the portion of the internet document associated with the user-generated highlight is a portion of the internet document that a user has highlighted via a highlighting service.

21. The computer-implemented method of claim 19, wherein the search query specifies a highlight source, and the documents satisfying the search query are those documents which contain the one or more search terms in a portion of the internet document that i) a person indicated by the highlight source has highlighted via the highlighting service, or a person belonging to a group indicated by the highlight source has highlighted via the highlighting service.

22. The computer-implemented method of claim 19, wherein the search query specifies a domain, and the documents satisfying the search query are those documents which are from the domain specified in the search query, and ii) which contain the one or more keywords in the portion of the internet document that a user has highlighted via a highlighting service.

23. The computer-implemented method of claim 19, wherein the search query specifies a rating, and the documents satisfying the search query are those documents which contain the one or more keywords in the portion of the internet document that a user has highlighted via a highlighting service, and wherein the portion of the internet document that the user has highlighted has been assigned a rating equal to or above the rating specified in the search query.

24. The computer-implemented method of claim 12, wherein the search query specifies one or more search terms, and the documents satisfying the search query are those documents which contain the one or more keywords in a comment associated with a user-generated highlight within the document.

25. A computer-implemented method comprising:

receiving a request for a document relevance score, wherein the document relevance score is based on an analysis of user-generated highlights; and

providing the document relevance score to a requesting service so as to enable the requesting service to utilize the document relevance score in assessing the relevance of a document.

26. The computer-implemented method of claim 25, wherein the requesting service is a search engine, and said search engine is to utilize the document relevance score in assessing the relevance of a document with respect to a search query received at the search engine.

27. The computer-implemented method of claim 25, wherein the request for the document relevance score includes a URL of a document to which the document relevance score is associated.

28. The computer-implemented method of claim 27, wherein the search results include internet documents which contain the one or more keywords in the portion of the internet document that a user has highlighted via the highlighting service.