Method and system for determining interest levels of online content based on rates of change of content access

• US 8,719,255 B1
• Filed: 09/28/2005
• Issued: 05/06/2014
• Est. Priority Date: 08/23/2005
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Pope, Elmore Eugene, Marshall, Brad E.
• Primary Examiner(s): Rostami, Mohammad S
• Application Number:
  US11/238,070
• Time in Patent Office: 3,142 Days
• Field of Search: None
• US Class Current: 707/716
• 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

A method and system for determining interest levels of online content based on rates of change of content access traffic. According to one embodiment, a method may include detecting content request traffic directed to a content source, determining a time rate of change of said content request traffic, and determining an indication of content interest associated with the content source, where the indication is dependent upon the time rate of change of the content request traffic. The method may further include storing the indication of content interest on a computer-accessible medium.

Claims

1. A method, comprising:

detecting content request traffic including a plurality of individual content requests directed to a content source, wherein each given one of the individual content requests corresponds to a respective referrer from which the given individual content request originated, such that each given one of the individual content requests corresponds to a respective path from a respective referrer to the content source, and wherein detecting content request traffic includes receiving a report of a content request from said content source via a web services interface;

for a plurality of distinct paths from respective referrers to the content source, determining a respective time rate of change of said content request traffic along each of said distinct paths, wherein said time rate of change of said content request traffic is indicative of a change in said content request traffic per unit of time, and wherein determining said time rate of change comprises numerically computing a derivative of said content request traffic with respect to time;

for each of the distinct paths, determining a respective indication of content interest, wherein said indication is dependent upon said time rate of change of said content request traffic along a corresponding one of the distinct paths; and

storing said indications of content interest associated with the distinct paths on a computer-accessible medium;

wherein each of said detecting content request traffic, said determining a respective time rate of change, said determining a respective indication of content interest, and said storing said indications of content interest is performed by one or more computer systems.

2. The method as recited in claim 1, wherein said content source includes a web site configured to provide web-based content.

3. The method as recited in claim 1, wherein said content request traffic includes content requests generated according to a web-based data transport protocol.

4. The method as recited in claim 3, wherein said web-based data transport protocol is compatible with a version of Hypertext Transfer Protocol (HTTP).

5. The method as recited in claim 1, wherein numerically computing said derivative comprises numerically computing a first derivative with respect to time of a time series of data points corresponding to said content request traffic.

6. The method as recited in claim 1, wherein numerically computing said derivative comprises numerically computing an Nth-order derivative with respect to time of a time series of data points corresponding to said content request traffic, wherein N is greater than 1.

7. The method as recited in claim 1, further comprising transforming a time series of data points corresponding to said content request traffic into a frequency domain.

8. The method as recited in claim 7, wherein said transforming includes performing a version of a Fast Fourier Transform algorithm on said time series of data points.

9. The method as recited in claim 1, wherein determining said indication of content interest includes normalizing said time rate of change of said content request traffic with respect to a volume of said content request traffic.

10. The method as recited in claim 9, wherein storing said indication of content interest includes storing said normalized time rate of change as said indication.

11. The method as recited in claim 1, wherein determining said indication of content interest includes mapping said time rate of change of said content request traffic to said indication using a first mapping function.

12. The method as recited in claim 11, wherein said first mapping function is configured to determine a new value of said indication dependent upon a current value of said indication.

13. The method as recited in claim 11, further comprising selecting said first mapping function from a plurality of mapping functions according to said time rate of change of said content request traffic.

14. The method as recited in claim 13, wherein said first mapping function is selected in response to determining that said time rate of change of said content request traffic is non-negative.

15. The method as recited in claim 14, further comprising selecting a second mapping function from said plurality of mapping functions in response to determining that said time rate of change of said content request traffic is negative.

16. The method as recited in claim 1, wherein said content source is included in a plurality of content sources, and wherein the method further comprises:

detecting respective content request traffic directed to each of said plurality of content sources;

determining a respective time rate of change of said content request traffic corresponding to each of said plurality of content sources;

determining a respective indication of content interest associated with each of said content sources, wherein said respective indication is dependent upon said respective time rate of change; and

storing said respective indication of content interest on a computer-accessible medium.

17. The method as recited in claim 16, wherein at least some of said respective indications of content interest are determined globally with respect to said plurality of content sources.

18. The method as recited in claim 16, wherein at least some of said respective indications of content interest are determined locally with respect to a subset of said plurality of content sources.

19. The method as recited in claim 18, wherein locally determining a given respective indication of content interest corresponding to a given content source is dependent upon a respective time rate of change of content request traffic directed to said given content source from one or more specified referrers.

20. The method as recited in claim 18, wherein locally determining a given respective indication of content interest corresponding to a given content source includes normalizing a global indication of content interest corresponding to said given content source with respect to respective global indications of content interest corresponding to said subset of said plurality of content sources.

21. The method as recited in claim 16, further comprising:

performing a search operation over said plurality of content sources, wherein at least a subset of said plurality of content sources satisfy criteria specified by said search operation; and

ranking said subset of said plurality of content sources according to said respective indications of content interest.

22. The method as recited in claim 1, further comprising retrieving a selected set of content interest data and returning said selected set to said content source via said web services interface in response to receiving said report.

23. The method as recited in claim 22, wherein said selected set is retrieved according to a data query specified in said report.

24. The method as recited in claim 1, further comprising:

determining whether a portion of said content request traffic originating from a given requestor exceeds a threshold frequency of content requests; and

dependent upon whether said portion of said content request traffic exceeds said threshold frequency, filtering said content request traffic to remove at least some of said portion of content request traffic prior to determining said indication of content interest.

25. The method as recited in claim 1, further comprising:

determining whether a portion of said content request traffic originating from a given requestor exhibits a manipulative pattern of content requests; and

dependent upon whether said portion of said content request traffic exhibits said manipulative pattern, filtering said content request traffic to remove at least some of said portion of content request traffic prior to determining said indication of content interest.

26. The method as recited in claim 1, further comprising:

determining whether said indication of content interest satisfies a notification criterion; and

if said indication satisfies said notification criterion, notifying a user.

27. The method as recited in claim 26, wherein notifying said user includes causing a dialog box to be displayed on a graphical interface associated with said user.

28. The method as recited in claim 26, wherein notifying said user includes causing an electronic mail to be sent to said user.

29. The method as recited in claim 26, wherein notifying said user includes notifying an RSS (Rich Site Summary) application associated with said user via a version of RSS protocol.

30. The method as recited in claim 1, further comprising selecting an advertisement for placement on said content source dependent upon said indication of content interest.

31. A non-transitory computer-accessible storage medium that stores instructions, wherein the instructions are executable to:

detect content request traffic including a plurality of individual content requests directed to a content source, wherein each given one of the individual content requests corresponds to a respective referrer from which the given individual content request originated, such that each given one of the individual content requests corresponds to a respective path from a respective referrer to the content source, and wherein to detect content request traffic directed to said content source, the instructions are further executable to receive a report of a content request from said content source via a web services interface;

for a plurality of distinct paths from respective referrers to the content source, determine a respective time rate of change of said content request traffic along each of said distinct paths, wherein said time rate of change of said content request traffic is indicative of a change in said content request traffic per unit of time, and wherein to determine said time rate of change, the instructions are further executable to numerically compute a derivative of said content request traffic with respect to time;

for each of the distinct paths, determine a respective indication of content interest, wherein said indication is dependent upon said time rate of change of said content request traffic along a corresponding one of the distinct paths; and

store said indication of content interest associated with the distinct paths.

32. The non-transitory computer-accessible storage medium as recited in claim 31, wherein said content source includes a web site configured to provide web-based content.

33. The non-transitory computer-accessible storage medium as recited in claim 31, wherein said content request traffic includes content requests generated according to a web-based data transport protocol.

34. The non-transitory computer-accessible storage medium as recited in claim 33, wherein said web-based data transport protocol is compatible with a version of Hypertext Transfer Protocol (HTTP).

35. The non-transitory computer-accessible storage medium as recited in claim 31, wherein to numerically compute said derivative, the instructions are further executable to numerically compute a first derivative with respect to time of a time series of data points corresponding to said content request traffic.

36. The non-transitory computer-accessible storage medium as recited in claim 31, wherein to numerically compute said derivative, the instructions are further executable to numerically compute an Nth-order derivative with respect to time of a time series of data points corresponding to said content request traffic, wherein N is greater than 1.

37. The non-transitory computer-accessible storage medium as recited in claim 31, wherein the instructions are further executable to transform a time series of data points corresponding to said content request traffic into a frequency domain.

38. The non-transitory computer-accessible storage medium as recited in claim 37, wherein to transform said time series of data points, the instructions are further executable to perform a version of a Fast Fourier Transform algorithm on said time series of data points.

39. The non-transitory computer-accessible storage medium as recited in claim 31, wherein to determine said indication of content interest, the instructions are further executable to normalize said time rate of change of said content request traffic with respect to a volume of said content request traffic.

40. The non-transitory computer-accessible storage medium as recited in claim 39, wherein to store said indication of content interest, the instructions are further executable to store said normalized time rate of change as said indication.

41. The non-transitory computer-accessible storage medium as recited in claim 31, wherein to determine said indication of content interest, the instructions are further executable to map said time rate of change of said content request traffic to said indication using a first mapping function.

42. The non-transitory computer-accessible storage medium as recited in claim 41, wherein said first mapping function is configured to determine a new value of said indication dependent upon a current value of said indication.

43. The non-transitory computer-accessible storage medium as recited in claim 41, wherein the instructions are further executable to select said first mapping function from a plurality of mapping functions according to said time rate of change of said content request traffic.

44. The non-transitory computer-accessible storage medium as recited in claim 43, wherein said first mapping function is selected in response to determining that said time rate of change of said content request traffic is non-negative.

45. The non-transitory computer-accessible storage medium as recited in claim 44, wherein the instructions are further executable to select a second mapping function from said plurality of mapping functions in response to determining that said time rate of change of said content request traffic is negative.

46. The non-transitory computer-accessible storage medium as recited in claim 44, wherein said content source is included in a plurality of content sources, and wherein the instructions are further executable to:

detect respective content request traffic directed to each of said plurality of content sources;

determine a respective time rate of change of said content request traffic corresponding to each of said plurality of content sources;

determine a respective indication of content interest associated with each of said content sources, wherein said respective indication is dependent upon said respective time rate of change; and

store said respective indication of content interest on a computer-accessible medium.

47. The non-transitory computer-accessible storage medium as recited in claim 46, wherein at least some of said respective indications of content interest are determined globally with respect to said plurality of content sources.

48. The non-transitory computer-accessible storage medium as recited in claim 46, wherein at least some of said respective indications of content interest are determined locally with respect to a subset of said plurality of content sources.

49. The non-transitory computer-accessible storage medium as recited in claim 48, wherein the instructions are further executable to locally determine a given respective indication of content interest corresponding to a given content source is dependent upon a respective time rate of change of content request traffic directed to said given content source from one or more specified referrers.

50. The non-transitory computer-accessible storage medium as recited in claim 48, wherein to locally determine a given respective indication of content interest corresponding to a given content source, the instructions are further executable to normalize a global indication of content interest corresponding to said given content source with respect to respective global indications of content interest corresponding to said subset of said plurality of content sources.

51. The non-transitory computer-accessible storage medium as recited in claim 46, wherein the instructions are further executable to:

perform a search operation over said plurality of content sources, wherein at least a subset of said plurality of content sources satisfy criteria specified by said search operation; and

rank said subset of said plurality of content sources according to said respective indications of content interest.

52. The non-transitory computer-accessible storage medium as recited in claim 31, wherein the instructions are further executable to retrieve a selected set of content interest data and return said selected set to said content source via said web services interface in response to receiving said report.

53. The non-transitory computer-accessible storage medium as recited in claim 52, wherein said selected set is retrieved according to a data query specified in said report.

54. The non-transitory computer-accessible storage medium as recited in claim 31, wherein the instructions are further executable to:

determine whether a portion of said content request traffic originating from a given requestor exceeds a threshold frequency of content requests; and

dependent upon whether said portion of said content request traffic exceeds said threshold frequency, filter said content request traffic to remove at least some of said portion of content request traffic prior to determining said indication of content interest.

55. The non-transitory computer-accessible storage medium as recited in claim 31, wherein the instructions are further executable to:

determine whether a portion of said content request traffic originating from a given requestor exhibits a manipulative pattern of content requests; and

dependent upon whether said portion of said content request traffic exhibits said manipulative pattern, filter said content request traffic to remove at least some of said portion of content request traffic prior to determining said indication of content interest.

56. The non-transitory computer-accessible storage medium as recited in claim 31, wherein the instructions are further executable to:

determine whether said indication of content interest satisfies a notification criterion; and

if said indication satisfies said notification criterion, notify a user.

57. The non-transitory computer-accessible storage medium as recited in claim 56, wherein to notify said user, the instructions are further executable to cause a dialog box to be displayed on a graphical interface associated with said user.

58. The non-transitory computer-accessible storage medium as recited in claim 56, wherein to notify said user, the instructions are further executable to cause an electronic mail to be sent to said user.

59. The non-transitory computer-accessible storage medium as recited in claim 56, wherein to notify said user, the instructions are further executable to notify an RSS (Rich Site Summary) application associated with said user via a version of RSS protocol.

60. The non-transitory computer-accessible storage medium as recited in claim 31, wherein the instructions are further executable to select an advertisement for placement on said content source dependent upon said indication of content interest.

61. A system, comprising one or more computer systems comprising one or more computer processors, the one or more computer systems configured to implement:

a web services interface configured to receive, according to a web services protocol, respective reports from a plurality of content sources of content request traffic directed to said content sources, wherein the content request traffic includes a plurality of individual content requests directed to a given one of the plurality of content sources, wherein each given one of the individual content requests corresponds to a respective referrer from which the given individual content request originated, such that each given one of the individual content requests corresponds to a respective path from a respective referrer to the given content source; and

a traffic analysis engine configured to receive said reports from said web services interface and to;

for a plurality of distinct paths from respective referrers to the given content source, determine a respective time rate of change of said content request traffic along each of said distinct paths, wherein for each given one of said distinct paths, said time rate of change of said content request traffic corresponding to said given path is indicative of a change, per unit of time, in said content request traffic along the given path to said given content source, and wherein to determine said respective time rate of change for said given path, the traffic analysis engine is further configured to numerically compute a derivative with respect to time of said content request traffic corresponding to said given path;

for each of the distinct paths, determine a respective indication of content interest, wherein said indication is dependent upon said respective time rate of change of said content request traffic along a corresponding one of the distinct paths; and

store said respective indication of content interest.

62. The system as recited in claim 61, wherein at least some of said content sources include a web site configured to provide web-based content.

63. The system as recited in claim 61, wherein said content request traffic includes content requests generated according to a web-based data transport protocol.

64. The system as recited in claim 63, wherein said web-based data transport protocol is compatible with a version of Hypertext Transfer Protocol (HTTP).

65. The system as recited in claim 61, wherein to numerically compute said derivative, said traffic analysis engine is further configured to numerically compute a first derivative with respect to time of a time series of data points corresponding to said content request traffic.

66. The system as recited in claim 61, wherein to numerically compute said derivative, said traffic analysis engine is further configured to numerically compute an Nth-order derivative with respect to time of a time series of data points corresponding to said content request traffic, wherein N is greater than 1.

67. The system as recited in claim 61, wherein said traffic analysis engine is further configured to transform a time series of data points corresponding to said content request traffic into a frequency domain.

68. The system as recited in claim 67, wherein to transform said time series of data points, said traffic analysis engine is further configured to perform a version of a Fast Fourier Transform algorithm on said time series of data points.

69. The system as recited in claim 61, wherein to determine said respective indication of content interest, said traffic analysis engine is further configured to normalize said time rate of change of said content request traffic with respect to a volume of said content request traffic of a corresponding content source.

70. The system as recited in claim 61, wherein said traffic analysis engine is further configured to retrieve a selected set of content interest data and return said selected set to a given content source via said web services interface in response to receiving a respective report from said given content source.

71. The system as recited in claim 70, wherein said traffic analysis engine is further configured to retrieve said selected set of content interest data according to a response type parameter of a web services call received by said web services interface and corresponding to said respective report.

72. The system as recited in claim 70, wherein said traffic analysis engine is further configured to retrieve said selected set of content interest data according to a free-form data query specified in said respective report.

73. The system as recited in claim 61, further comprising a downloadable interest data display module, wherein said interest data display module is executable by a host computer system to display content interest data retrieved from said traffic analysis engine by said host computer system via said web services interface.

74. The system as recited in claim 61, wherein said web services protocol implements a representational state transfer (REST) web services model.

75. The system as recited in claim 74, wherein to receive a given respective report according to said web services protocol, said web services interface is further configured to receive a request formatted according to a version of Hypertext Transfer Protocol (HTTP), wherein contents of said given respective report are included in said request as parameters formatted according to a version of eXtensible Markup Language (XML).

76. The system as recited in claim 61, wherein said web services protocol implements a document-based web services model.

77. The system as recited in claim 76, wherein to receive a given respective report according to said web services protocol, said web services interface is further configured to receive a document encapsulated according to a version of Simple Object Access Protocol (SOAP), wherein contents of said given respective report are included in said document and formatted according to a version of XML.