Methods and systems for improving a search ranking using article information

• US 8,954,420 B1
• Filed: 03/31/2004
• Issued: 02/10/2015
• Est. Priority Date: 12/31/2003
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Khan, Omar Habib, Lawrence, Stephen R.
• Primary Examiner(s): Mofiz, Apu
• Assistant Examiner(s): Khoshnoodi, Fariborz
• Application Number:
  US10/814,357
• Time in Patent Office: 3,968 Days
• Field of Search: 707/7, 707/3, 707/5, 707/9, 707/722, 707/723, 713/200
• US Class Current: 707/722
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

Systems and methods that improve client-side searching are described. In one aspect, a system and method for identifying an article, and determining a ranking score for the article based at least in part on duration data, access data, URL data, or trajectory data associated with the article is described.

Claims

1. A method performed by a computer, comprising:

identifying an article;

receiving trajectory data associated with the article indicating whether the article is a web page that started a user on a sequence of associated web pages;

determining a ranking score for the article based at least in part on the trajectory data associated with the article, wherein the ranking score is higher responsive at least in part to a positive indication that the article is a web page that started the user on a sequence of associated web pages;

arranging the article with at least one other article in a ranking order responsive at least in part to the ranking score; and

presenting the arranged articles to a user in the ranking order.

2. The method of claim 1, wherein the article is a client-side article.

3. The method of claim 1, wherein the article is a network article.

4. The method of claim 1, wherein identifying the article comprises receiving user behavior associated with the article.

5. The method of claim 1, wherein identifying the article comprises receiving a search query and determining the article to be relevant to the search query.

6. The method of claim 1, wherein identifying the article comprises identifying a frequently accessed article for a one-click-away page.

7. The method of claim 1, wherein receiving trajectory data comprises determining a login page as the start of a trajectory.

8. The method of claim 1, wherein receiving trajectory data comprises determining a logout page as the end of the trajectory.

9. The method of claim 1, wherein an article at a beginning of a trajectory is ranked higher than an article at an end of a trajectory.

10. The method of claim 1, wherein receiving trajectory data comprises determining an article.

11. A computer-readable storage medium containing computer-executable program code comprising:

program code for identifying an article;

program code for receiving trajectory data associated with the article indicating whether the article is a web page that started a user on a sequence of associated web pages;

program code for determining a ranking score for the article based at least in part on the trajectory data associated with the article, wherein the ranking score is higher responsive at least in part to a positive indication that the article is a web page that started the user on a sequence of associated web pages;

program code for arranging the article with at least one other article in a ranking order responsive at least in part to the ranking score; and

program code for presenting the arranged articles to a user in the ranking order.

12. The computer-readable medium of claim 11, wherein the article is a client-side article.

13. The computer-readable medium of claim 11, wherein the article is a network article.

14. The computer-readable medium of claim 11, wherein identifying the article comprises receiving user behavior associated with the article.

15. The computer-readable medium of claim 11, wherein identifying the article comprises receiving a search query and determining the article to be relevant to the search query.

16. The computer-readable medium of claim 11, wherein identifying the article comprises identifying a frequently accessed article for a one-click-away page.

17. The computer-readable medium of claim 11, wherein receiving trajectory data comprises determining a login page as the start of a trajectory.

18. The computer-readable medium of claim 11, wherein receiving trajectory data comprises determining a logout page as the end of a trajectory.

19. The computer-readable medium of claim 11, wherein an article at a beginning of a trajectory is ranked higher than an article at an end of a trajectory.

20. The computer-readable medium of claim 11, wherein the trajectory data comprises determining an article.

21. A computer system, comprising:

a processor for executing computer program instructions;

a computer-readable storage medium having computer-executable program instructions embodied therein comprising;

means for identifying an article;

means for receiving trajectory data associated with the article indicating whether the article is a web page that started a user on a sequence of associated web pages;

means for determining a ranking score for the article based at least in part on the trajectory data associated with the article, wherein the ranking score is higher responsive at least in part to a positive indication that the article is a web page that started the user on a sequence of associated web pages;

means for arranging the article with at least one other article in a ranking order responsive at least in part to the ranking score; and

means for presenting the arranged articles to a user in the ranking order.

22. The system of claim 21 further comprising:

means for receiving a search query; and

means for determining the article is relevant to the search query.

23. The system of claim 21, wherein identifying the article comprises identifying the article for a one-click-away page.

24. A method performed by a computer, comprising:

receiving a query signal from a query processor;

determining trajectory data associated with one or more articles within a set of articles responsive at least in part to the query signal and a client behavior database, wherein the trajectory data comprise an indication of whether the article is a web page that started a user on a sequence of associated web pages;

determining a ranking score for the article based at least in part on the trajectory data, wherein the ranking score is higher responsive at least in part to a positive indication that the article is a web page that started the user on a sequence of associated web pages;

arranging the one or more articles in a ranking order based at least in part on the ranking score; and

causing output of the one or more articles.

25. A method performed by a computer to provide ranked articles, comprising:

identifying one or more articles;

receiving user behavior data associated with the one or more articles;

determining trajectory data responsive at least in part to the user behavior data, wherein the trajectory data indicate whether an article of the one or more articles is a web page that started a user on a sequence of associated web pages;

determining a ranking score for each of the one or more articles based at least in part on the trajectory data, wherein the ranking score is higher responsive at least in part to a positive indication that the article is a web page that started the user on a sequence of associated web pages;

arranging the one or more articles in a ranking order responsive at least in part to the one or more ranking scores; and

presenting the arranged one or more articles to a user in the ranking order.

26. The method of claim 25, wherein the one or more articles is comprised of one or more HTML files, XML files, XHTML files, PDF files, word processor files, database files, application document files, chat messages, email messages, audio files, or video files.

27. The method of claim 25, wherein the user behavior data indicate a number of times the user views the one or more articles.

28. The method of claim 25, wherein the user behavior data indicate an amount of time spent by the user viewing the one or more articles.

29. The method of claim 25, wherein the user behavior data indicate an amount of time elapsed since the one or more articles were last accessed by the user.

30. The method of claim 25, wherein the user behavior data indicate a time of day in which the one or more articles were accessed by the user.

31. The method of claim 25, wherein the user behavior data indicate a day of the week in which the one or more articles were accessed by the user.

32. The method of claim 25, wherein the trajectory data further indicate whether the article is a web page acting as an article hub to which the user frequently returned as a source of links for other articles and wherein the ranking score for the article is higher responsive at least in part to a positive indication that the article is an article hub.

33. The method of claim 25, wherein the trajectory data further indicate that the article is a web page acting as an article hub to which the user frequently returned as a source of links for other articles, wherein the user behavior data indicate a sum of time spent on individual articles linked to the article acting as the article hub, and wherein the ranking score is determined responsive at least in part to the sum of time.

34. The method of claim 25, wherein the ranking score for an article is an approximation of the importance of the article to the user relative to one or more other articles.

35. A computer system, for providing ranked articles, comprising:

a processor for executing computer program instructions;

a computer-readable storage medium having computer-executable program instructions embodied therein comprising;

an article locator for identifying one or more articles;

a client behavior data processor for receiving user behavior data associated with the one or more articles and determining trajectory data responsive at least in part to the user behavior data, wherein the trajectory data comprise an indication of whether an article of the one or more articles is a web page that started a user on a sequence of associated web pages; and

a ranking processor for determining a ranking score for each of the one or more articles based at least in part on the trajectory data, wherein the ranking score for the article is higher responsive at least in part to a positive indication that the article is a web page that started the user on a sequence of associated web pages, arranging the one or more articles in a ranking order responsive at least in part to the one or more ranking scores, and presenting the arranged one or more articles to a user in the ranking order.

36. The computer system of claim 35, wherein the one or more articles is comprised of one or more HTML files, XML files, XHTML files, PDF files, word processor files, database files, application document files, chat messages, email messages, audio files, or video files.

37. The computer system of claim 35, wherein the user behavior data indicate a number of times the user views the one or more articles.

38. The computer system of claim 35, wherein the user behavior data indicate an amount of time spent by the user viewing the one or more articles.

39. The computer system of claim 35, wherein the user behavior data indicate an amount of time elapsed since the one or more articles were last accessed by the user.

40. The computer system of claim 35, wherein the user behavior data indicate a time of day in which the one or more articles were accessed by the user.

41. The computer system of claim 35, wherein the user behavior data indicate a day of the week in which the one or more articles were accessed by the user.

42. The computer system of claim 35, wherein the trajectory data further indicate whether the article is a web page acting as an article hub to which the user frequently returned as a source of links for other articles and wherein the ranking score for the article is higher responsive at least in part to a positive indication that the article is an article hub.

43. The computer system of claim 42, wherein the trajectory data indicate that the article is a web page acting as an article hub to which the user frequently returned as a source of links for other articles, wherein the user behavior data indicate a sum of time spent on individual articles linked to the article acting as the article hub, and wherein the ranking score is determined responsive at least in part to the sum of time.

44. The computer system of claim 35, wherein the ranking score for an article is an approximation of the importance of the article to the user relative to one or more other articles.

45. A computer program product having a computer-readable storage medium having computer-executable program instructions embodied therein for providing ranked articles, comprising:

a software portion configured to identify one or more articles;

a software portion configured to receive user behavior data associated with the one or more articles;

a software portion configured to determine trajectory data responsive at least in part to the user behavior data, wherein the trajectory data comprise an indication of whether an article of the one or more articles is a web page that started a user on a sequence of associated web pages;

a software portion configured to determine a ranking score for each of the one or more articles based at least in part on the trajectory data, wherein the ranking score for the article is higher responsive at least in part to a positive indication that the article is a web page that started the user on a sequence of associated web pages;

a software portion configured to arrange the one or more articles in a ranking order responsive at least in part to the one or more ranking scores; and

a software portion configured to present the arranged one or more articles to a user in the ranking order.

46. The computer program product of claim 45, wherein the one or more articles is comprised of one or more HTML files, XML files, XHTML files, PDF files, word processor files, database files, application document files, chat messages, email messages, audio files, or video files.

47. The computer program product of claim 45, wherein the user behavior data indicate a number of times the user views the one or more articles.

48. The computer program product of claim 45, wherein the user behavior data indicate an amount of time spent by the user viewing the one or more articles.

49. The computer program product of claim 45, wherein the user behavior data indicate an amount of time elapsed since the one or more articles were last accessed by the user.

50. The computer program product of claim 45, wherein the user behavior data indicate a time of day in which the one or more articles were accessed by the user.

51. The computer program product of claim 45, wherein the user behavior data indicate a day of the week in which the one or more articles were accessed by the user.

52. The computer program product of claim 45, wherein the trajectory data indicate whether the article is a web page acting as an article hub to which the user frequently returned as a source of links for other articles and wherein the ranking score for the article is higher responsive at least in part to a positive indication that the article is an article hub.

53. The computer program product of claim 52, wherein the trajectory data indicate that the article is a web page acting as an article hub to which the user frequently returned as a source of links for other articles, wherein the user behavior data indicate a sum of time spent on individual articles linked to the article acting as the article hub, and wherein the ranking score is determined responsive at least in part to the sum of time.

54. The computer program product of claim 45, wherein the ranking score for an article is an approximation of the importance of the article to the user relative to one or more other articles.