Automatic mapping of a location identifier pattern of an object to a semantic type using object metadata

• US 8,200,617 B2
• Filed: 06/22/2009
• Issued: 06/12/2012
• Est. Priority Date: 04/15/2009
• Status: Active Grant

• Current Assignee: Fiver LLC
• Original Assignee: EVRI Incorporated
• Inventors: Spivack, Nova T., Wissner, James M., White, Scott
• Primary Examiner(s): Quader, Fazlul
• Application Number:
  US12/489,352
• Publication Number:
  US 20100268720A1
• Time in Patent Office: 1,086 Days
• Field of Search: 707/602
• US Class Current: 707/602
• CPC Class Codes: G06F 16/3334 Selection or weighting of terms from queries, including natural language queries
• CPC Class Codes: G06F 16/3337 Translation of the query language, e.g. Chinese to English
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/81 Indexing, e.g. XML tags; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/86 Mapping to a database
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06F 16/986 Document structures and storage, e.g. HTML extensions
• CPC Class Codes: G06F 40/143 Markup, e.g. Standard Generalized Markup Language [SGML] or Document Type Definition [DTD]
• CPC Class Codes: G06F 40/186 Templates
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

Systems and methods for automatic mapping of a location identifier pattern of an object to a semantic type using object metadata are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of identifying a set of tags associated with a website that is hosted by a web server. The method further includes, detecting a web page in the website in which a tag of the set of tags is identified, extracting a pattern from a Universal Resource Locator (URL) of the web page, and/or storing the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type. The tag corresponds to a semantic type with which the content embodied in the web page has a semantic relationship and the pattern corresponds to the semantic type with which the content embodied in the web page has a semantic relationship.

Claims

1. A method for automatically mapping a pattern of a location identifier of an object to a semantic type using metadata associated with the object, the method, comprising:

determining the location identifier for the object;

wherein, the metadata corresponds to the semantic type with which the object or content embodied therein has a semantic relationship;

extracting the pattern from the location identifier of the object;

storing the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type;

wherein, the pattern corresponds to the semantic type with which the object or the content embodied therein has a semantic relationship;

wherein, the metadata has an associated weighting; and

wherein, the pattern extracted from the location identifier has a trustworthiness rating that corresponds to the associated weighting of the metadata.

2. The method of claim 1, further comprising,

retrieving the pattern from the database;

wherein, the pattern is used to search for other location identifiers also having the pattern for locating other objects or other objects having content embodied therein, that have the semantic relationship to the semantic type.

3. The method of claim 2, further comprising:

receiving a search query via a user interface;

mapping the search query into the pattern; and

performing a search for the other location identifiers also having the pattern.

4. The method of claim 1,

further comprising, collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself;

wherein, each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier.

5. The method of claim 4, wherein, the metadata is collected from web content including one or more of, bookmarked content and blog articles.

6. The method of claim 4, wherein, the metadata is collected from a social networking site.

7. The method of claim 4, wherein, the metadata is collected from analyzing user behavior.

8. The method of claim 4, wherein, the metadata includes user-generated or user-identified metadata.

9. The method of claim 8, wherein, the user-generated or user-identified metadata includes one or more tags.

10. The method of claim 8, wherein, the user-generated or user-identified metadata includes user reviews or user annotation.

11. The method of claim 4, further comprising,

analyzing multiple tags identified from the plurality of content sources;

selecting a subset of the multiple tags for use in identifying a set of semantic types with which the object or the content embodied therein has a semantic relationship.

12. The method of claim 11, further comprising,

identifying the set of semantic types, each of which corresponds to one or more of the subset of the multiple tags;

identifying each of the set of semantic types in the database embodied in the machine-readable storage medium as being mapped to the pattern stored therein;

wherein, the pattern corresponds to the each of the set of semantic types with which the object or the content embodied therein has a semantic relationship.

13. The method of claim 12, further comprising, indexing the location identifier as being mapped to each of the set of semantic types.

14. The method of claim 11, further comprising, assigning weights to each of the multiple tags.

15. The method of claim 11, wherein, a weight for a particular tag of the multiple tags is assigned based a rating of a user who identified the particular tag.

16. The method of claim 15, wherein, the rating of the user is determined based on an interest of the user.

17. The method of claim 15, wherein, the rating of the user is determined based on one or more of, social endorsement of the user by other users, expertise of the user, and reliability of the user.

18. The method of claim 15, wherein, the rating of the user is determined based on similarity of tags identified by the user compared to tags identified by other users for a same set of content.

19. The method of claim 12, wherein, the subset of the multiple tags is selected based on the weights assigned to each of the multiple tags.

20. The method of claim 19, wherein, each of the subset of the multiple tags are selected when a usage frequency of a particular tag exceeds a threshold value.

21. The method of claim 20, wherein, the usage frequency of the particular tag is a number of times or a percentage of times the object or the content embodied in the object has been associated with a particular tag.

22. The method of claim 1,

wherein, the object is a web page;

wherein, the location identifier is a Universal Resource Locator (URL).

23. The method of claim 22, further comprising,

identifying a second URL having a same domain as the location identifier;

wherein, the second URL links to a second web page having content embodied therein that is also associated with the metadata;

extracting the pattern by comparing the URL with the second URL.

24. The method of claim 1, wherein, the object is visually sorted in a search results page according to the semantic relationship with the semantic type.

25. The method of claim 1, wherein, the semantic relationship specifies a type of thing or concept that the content embodied in the object is relevant to.

26. The method of claim 25, wherein, the semantic relationship includes, an “

is-a”

relationship.

27. The method of claim 1, wherein, the semantic relationship specifies a type of format that the content embodied in the object is of.

28. The method of claim 27, wherein, the semantic relationship includes, a “

has-format”

relationship.

29. The method of claim 1, wherein, the semantic relationship specifies a type of audience that the content embodied in the object is intended for.

30. The method of claim 29, wherein, the semantic relationship includes, a “

has-udience”

relationship.

31. The method of claim 1, wherein, the semantic relationship specifies a language that the content embodied in the object is in.

32. The method of claim 31, wherein, the semantic relationship includes, an “

of-language”

relationship.

33. The method of claim 1, wherein, the semantic relationship specifies a set of semantic tags that the content embodied in the object is relevant to.

34. The method of claim 1, wherein, the semantic relationship specifies a web site where the object is from.

35. The method of claim 34, wherein, the semantic relationship includes, a “

has-domain”

relationship.

36. The method of claim 1, wherein, the semantic relationship specifies popularity of the content embodied in the object.

37. A method for automatically mapping a pattern in a URL of a web page in a website to a tangible entity or intangible concept, the method, comprising:

identifying a set of tags associated with a website that is hosted by a web server;

detecting, from the website, a web page with which a tag of the set of tags is associated;

wherein, the tag corresponds to the tangible entity or intangible concept with which the content embodied in the web page has a relationship;

extracting a pattern from a Universal Resource Locator (URL) of the web page;

storing the pattern in a database embodied in a machine-readable storage medium as being mapped to the tangible entity or intangible concept;

wherein, the pattern corresponds to the tangible entity or intangible concept with which the content embodied in the web page has a relationship;

wherein, the tag has an associated weight value; and

rating trustworthiness of the pattern extracted from the URL based on the associated weight value of the tag that is identified in the web page having the URL.

38. The method of claim 37, wherein, the relationship specifies a type of thing or concept that the content embodied in the web page is relevant to.

39. The method of claim 37, wherein, the relationship specifies a type of format that the content embodied in the web page is of.

40. The method of claim 37, wherein, the relationship specifies a type of audience that the content embodied in the web page is intended for.

41. The method of claim 37, wherein, the relationship specifies a language that the content embodied in the web page is in.

42. The method of claim 37, wherein, the relationship specifies a set of semantic tags that the content embodied in the web page is relevant to.

43. The method of claim 37, wherein, the relationship specifies a domain where the web page is from.

44. The method of claim 37, further comprising, sorting the web page in a search results page such that the web page visually appears to be associated with the tangible entity or intangible concept in response to receiving a user request.

45. The method of claim 37, wherein, the tangible entity or intangible concept is represented by a semantic type.

46. The method of claim 45, further comprising:

for each of the set of tags, identifying at least one web page in the website with which each of the set of tags is associated;

determining a set of semantic types each of which corresponds to each of the set of tags;

extracting a set of patterns from URLs of each of the at least one web page;

storing each of the set of patterns in a machine-readable storage medium as being mapped each of the set of semantic types;

wherein, each of the set of pattern corresponds to each of the set of semantic types with which content embodied in each of the at least one web page has a semantic relationship.

47. A method for automatically mapping patterns of URLs of web pages on a website to one or more semantic types using a tag, the method, comprising:

identifying a first web page and a second web page in the web site;

retrieving a first URL of the first web page and a second URL of the second web page;

storing the first and second URLs in memory for analysis;

comparing URL segments in the first and second URLs and corresponding values in each field;

extracting a first pattern by identifying a key field from the URL segments in the first URL;

using the key field, identifying a first semantic type with which content embodied in the first web page has a first type of semantic relationship;

storing the first pattern in a database embodied in a machine-readable storage medium as being mapped to the first semantic type;

wherein, the tag has an associated weight value; and

rating trustworthiness of the pattern extracted from the URL based on the associated weight value of the tag that is identified in the web page having the URL.

48. The method of claim 47,

further comprising, determining a template structure of the first web page based on the comparison;

wherein, the key field determines a layout of the template structure;

wherein, the first semantic type is identified from the layout of the template structure.

49. The method of claim 48, further comprising,

identifying, from one or more of, the key field, another key field, and the layout, another semantic type;

wherein, the content embodied in the first web page has another type of semantic relationship with the another semantic type.

50. The method of claim 47, further comprising,

identifying, using a tag associated with the first web page, a third semantic type;

wherein, the content embodied in the first web page has a third type of semantic relationship with the third semantic type.

51. The method of claim 47, further comprising:

using the first pattern, extracting a value from the key field of the URL segments in the second URL;

identifying, based on the value in the key field, a second semantic type with which content embodied in the second web page has the first type of semantic relationship.

52. The method of claim 47, wherein, the first and second web pages are item detail pages.

53. The method of claim 47, wherein, the web site is selected from a set of candidate web sites.

54. The method of claim 53, wherein, the web site is selected from the set of candidate web sites based on user behavior related to the web site.

55. The method of claim 54, wherein, the user behavior includes, one or more of, number of user visits and number of bookmarks of web pages in the web site.

56. The method of claim 54, wherein, the user behavior includes, one or more of, number of shares with other users and number of mentions via a social networking utility.

57. A method for mapping patterns of location identifiers of web pages to a semantic type using a tag, the method, comprising:

selecting the tag from multiple tags associated with an initial content source;

using the tag as a search query in locating a set of search results using a search engine;

identifying a set of location identifiers each of which corresponds to one of the set of search results;

extracting a set of patterns from each of the set of location identifiers;

storing the set of patterns in a machine-readable storage medium as being mapped to a semantic type corresponding to the tag;

wherein, each of the set of patterns corresponds to the semantic type with which content embodied in each of the set of search results has a semantic relationship;

assigning a weight to each of the tag;

wherein, the pattern extracted from the location identifier has a trustworthiness rating that corresponds to the associated weighting of the tag.

58. The method of claim 57, wherein, the set of search results is selected from a larger pool of search results identified using the search query.

59. The method of claim 57, wherein, the tag is selected in response to determining that the location identifier of the initial content source includes a segment having the tag.

60. The method of claim 57, wherein, the tag is selected in response to determining that the initial content source includes text comprising the tag.

61. The method of claim 57, wherein, the tag is selected in response to determining that XHTML or HTML of the initial content source includes text comprising the tag.

62. A system for automatically mapping a pattern in a URL of a web page in a website to a semantic type, the system, comprising:

a metadata identifier module that identifies a set of tags associated with a website that is hosted by a web server;

an object finder module that detects a web page in the website in which a tag of the set of tags is identified;

a type detection module that determines a semantic type with which the tag corresponds;

wherein, the content embodied in the web page has a semantic relationship with the semantic type that corresponds to the tag;

an extraction module that extracts a pattern from a Universal Resource Locator (URL) of the web page;

wherein, the pattern corresponds to the semantic type with which the content embodied in the web page has a semantic relationship;

a weighting module that assigns a weight to each of the tag;

wherein, the pattern extracted from the location identifier has a trustworthiness rating that corresponds to the associated weighting of the tag.

63. The system of claim 62, further comprising,

a metadata analyzer that analyzes the set of tags;

and

a metadata filter module that selects the tag from the set of tags for use in determining the semantic type to which the pattern extracted from the URL corresponds.

64. A machine-readable storage medium having stored thereon a set of instructions which when executed perform a method for automatically mapping a pattern of a location identifier of an object to a semantic type using metadata associated with the object, comprising:

collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself;

wherein, each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier determining the location identifier for the object;

wherein, the metadata corresponds to the semantic type with which the object or content embodied therein has a semantic relationship;

extracting the pattern from the location identifier of the object;

storing the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type;

wherein, the pattern corresponds to the semantic type with which the object or the content embodied therein has a semantic relationship;

wherein, the metadata has an associated weighting; and

wherein, the pattern extracted from the location identifier has a trustworthiness rating that corresponds to the associated weighting of the metadata.