Search and search optimization using a pattern of a location identifier

• US 8,862,579 B2
• Filed: 04/14/2010
• Issued: 10/14/2014
• Est. Priority Date: 04/15/2009
• Status: Expired due to Fees

• Current Assignee: Fiver LLC
• Original Assignee: VCVC III LLC (Vulcan, Inc.)
• Inventors: Spivack, Nova, Wissner, James M.
• Primary Examiner(s): Ahn, Sangwoo
• Application Number:
  US12/760,387
• Publication Number:
  US 20100268700A1
• Time in Patent Office: 1,644 Days
• US Class Current: 707/731
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/367 Ontology
• 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
• CPC Class Codes: G06F 2216/03 Data mining
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

Systems and methods for search and search optimization using a pattern in a location identifier is disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of search and search optimization. The method includes, detecting a set of location identifiers that have a pattern that matches a specified pattern and identifying a set of search results as having content related to the semantic type. The specified pattern can be stored in a computer-readable storage medium and corresponds to a semantic type. The set of search results can include objects associated with the set of location identifiers having the specified pattern.

Claims

1. A method for optimizing search, the method, comprising:

identifying a location identifier of a webpage having content associated with a semantic type;

extracting a pattern from the location identifier of the webpage that is different from the location identifier but including a portion of the location identifier;

storing the pattern in a computer database embodied in a computer-readable storage medium;

wherein, the pattern corresponds to a semantic type of the content in the webpage;

using the pattern stored in the computer-readable storage medium, performing pattern recognition on multiple location identifiers having a same domain name as the location identifier;

detecting location identifiers from the multiple location identifiers matching the pattern extracted from the location identifier;

identifying, a set of type-determined web pages having the matching location identifiers;

wherein, each of the set of type-determined web pages has content that is related to the semantic type;

wherein, the semantic type is associated with multiple attributes that are user-defined;

wherein, the pattern is extracted from the location identifier using user input;

data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic type; and

identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining.

2. The method of claim 1, wherein, the location identifier is a Universal Resource Identifier (URI) or Universal Resource Locator (URL).

3. The method of claim 1, further comprising, generating a set of search results from the set of type-determined web pages.

4. The method of claim 1, further comprising, associating each of the set of type-determined web-pages with an ontology defining the semantic type.

5. The method of claim 3, further comprising,

extracting additional semantic data from HTML or XHTML content of each of the set of type-determined web pages;

and

generating a refined set of search results from the set of search results using the additional semantic data.

6. The method of claim 5, wherein, the additional semantic data is extracted using GRDDL (Gleaning Resource Descriptions from Dialects of Languages).

7. The method of claim 3, further comprising,

generating a refined set of search results from the refined set of type-determined web pages.

8. The method of claim 7, further comprising, ranking each of the set of type-determined web pages based on the relevancy determined from the data mining.

9. The method of claim 1, wherein, the multiple location identifiers are identified from a sitemap.

10. The method of claim 1, further comprising, automatically parsing the location identifier to extract the pattern based on the semantic type.

11. The method of claim 1, wherein, the multiple attributes are rated by users via a user interface.

12. The method of claim 1, wherein, the semantic type of the content of the webpage is automatically determined.

13. The method of claim 1, wherein, the semantic type of the content of the webpage is defined by an end user.

14. The method of claim 13, wherein, the semantic type is defined by the end user through tagging or annotating the webpage on a user interface.

15. The method of claim 13, wherein, the pattern corresponding to the semantic type is determined when the webpage is identified as having the content of the semantic type by the end user.

16. The method of claim 13, further comprising, identifying multiple patterns corresponding to the semantic type based on identification of multiple webpages as having content of the semantic type by the end user or additional end users.

17. The method of claim 1, wherein, some of the multiple attributes are automatically determined.

18. The method of claim 1, wherein, the pattern further corresponds to an attribute of the semantic type of the content in the webpage.

19. The method of claim 17, wherein, some of the multiple attributes of the semantic type are determined by a predefined ontology.

20. The method of claim 18, wherein, each of the type-determined web pages includes content that is associated with the attribute of the semantic type.

21. The method of claim 1, wherein, some of the multiple attributes of the semantic type are determined by a user defined ontology.

22. The method of claim 1, wherein, the pattern includes a domain name segment or a wildcard segment.

23. The method of claim 22, wherein, the pattern further includes a semantic type segment.

24. The method of claim 22, wherein, the pattern further includes an attributes segment.

25. The method of claim 1, further comprising:

extracting a sub-pattern from the location identifier of the webpage;

wherein, the sub-pattern corresponds to an attribute of the semantic type of the content.

26. The method of claim 25, further comprising:

using the sub-pattern, performing pattern recognition on the multiple location identifiers;

detecting a subset of the matching location identifiers having a same pattern as the sub-pattern; and

identifying a subset of the type-determined web pages having the subset of the matching location identifiers;

wherein, each of the subset of the type-determined web pages includes content associated with the attribute of the semantic type.

27. The method of claim 1, further comprising:

extracting multiple sub-patterns from the location identifier;

wherein, each of the multiple sub-patterns corresponds to one of the multiple attributes of the semantic type; and

identifying multiple subsets of the set of the type-determined web pages using the multiple sub-patterns;

wherein, each of the multiple subsets of the type-determined web pages includes content associated with one of the multiple attributes of the semantic type.

28. The method of claim 27, further comprising:

presenting, on a first page of a user interface, the type-determined web pages categorized as having the semantic type;

presenting, on the first page of the user interface, links to each of the multiple subsets of the type-determined web pages that are associated with one of the multiple attributes of the semantic type;

wherein, each of the links are identified, on the first page, by each of the multiple attributes; and

presenting, on a second page of the user interface, another set of type-determined web pages as categorized as having another semantic type.

29. The method of claim 1, further comprising:

presenting, a type-determined web page that is hosted by a sponsoring domain, as a search result that has a differentiating template.

30. The method of claim 1, further comprising:

performing pattern recognition using the pattern on additional location identifiers having a different domain name than the location identifier;

detecting an additional set of matching location identifiers from the additional location identifiers having the pattern extracted from the location identifier; and

generating an additional set of search results including an additional set of type-determined web pages having the additional set of matching location identifiers;

wherein, each of the additional set of type-determined web pages has content associated with the semantic type.

31. A method of search, the method, comprising:

detecting a set of location identifiers of webpages that match a specified pattern that is not a unified resource identifier (URI), the specified pattern being stored in a computer-readable storage medium;

wherein, the specified pattern corresponds to a semantic type;

identifying a set of search results as having content related to the semantic type;

identifying a set of type-determined webpages having the matching location identifiers;

data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic type;

identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining;

generating a refined set of search results from the refined set of type-determined web pages; and

ranking each of the set of type-determined web pages based on the relevancy determined from the data mining;

wherein, the semantic type is associated with multiple attributes that are user-defined; and

wherein, the set of search results includes objects associated with the set of location identifiers having the specified pattern.

32. The method of claim 31, further comprising, linking the objects to an ontology defining the semantic type.

33. The method of claim 31,

wherein, the location identifier is a Universal Resource Identifier (URI) or Universal Resource Locator (URL);

and

wherein, the objects are web pages.

34. The method of claim 31, further comprising,

data mining the content of each of the set of search results to further determine relevancy to the semantic type;

and

identifying a refined set of search results from the set of type-determined web pages based on the relevancy to the semantic type determine via the data mining.

35. The method of claim 34, further comprising, ranking each of the set of search results based on the relevancy determined from the data mining.

36. The method of claim 31, wherein, the set of location identifiers are identified from links of user-added content in a social network.

37. The method of claim 31, wherein, the specified pattern is automatically identified by performing pattern recognition using parameters determined from the semantic type.

38. The method of claim 31, wherein, the specified pattern is manually specified and reconfigurable.

39. A method for optimizing search, the method, comprising:

identifying a pattern template followed in one or more Universal Resource Identifiers (URIs), the pattern template including multiple specified patterns not being URIs but respectively corresponding to a plurality of semantic object types;

wherein, at least some of the plurality of semantic object types are associated with attributes that are user-defined;

storing the pattern template in a computer database embodied in a computer-readable storage medium for use in subsequent searches;

providing a user interface that enables a user to perform searching;

receiving a search query via the user interface;

retrieving the pattern template from the computer database;

mapping the search query into a specified pattern of the multiple specified patterns;

performing a search for URIs that match the specified pattern;

identifying, a set of type-determined web pages having the matching URIs;

wherein, each of the set of type-determined web pages has content that is related to the semantic object type to which the specified pattern correspond;

data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic object type; and

identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic object type determined via the data mining.

40. The method of claim 39, further comprising, presenting web pages corresponding to the matching URIs as search results to the user.

41. A method for optimizing search using semantics, the method, comprising:

identifying a Universal Resource Identifier (URI) of a webpage having content associated with a semantic type that is specified by a user;

identifying a pattern, from the URI of the webpage that is different from the URI but including a portion of the URI that corresponds to the semantic type;

storing the pattern in a computer-readable storage medium;

wherein, the pattern is identified from the URI using user input;

identifying additional patterns for the semantic type based on identification of additional webpage as having content of the semantic type;

storing the additional patterns in the computer-readable storage medium;

using the pattern and the additional patterns, performing pattern recognition on multiple URIs;

detecting URIs from the multiple URIs matching the pattern extracted from the URI;

identifying a set of type-determined web pages having the matching URIs;

wherein, each of the set of type-determined web pages has content that is of the semantic type,

wherein, the semantic type is associated with multiple attributes that are user-defined;

data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic type; and

identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining.

42. The method of claim 41, further comprising, ranking each of the additional patterns identified for the semantic type based on a number of users that identified each of the additional web pages as having content of the semantic type.

43. The method of claim 41, wherein, the semantic type is defined by the user through tagging the webpage on a user interface.

44. The method of claim 41, further comprising:

identifying multiple sub-patterns from the URI using multiple attributes of the semantic type defined by the user or other users.

45. The method of claim 44, further comprising:

identifying multiple subsets of the set of type-determined web pages using the multiple sub-patterns;

wherein, each of the multiple subsets of type-determined web pages includes content associated with one of the multiple attributes of the semantic type.

46. The method of claim 41,

wherein, the webpage is identified by a second user as having content of a second semantic type that is different from the semantic type and is specified by the second user;

identifying a second pattern, from the URI of the webpage, that corresponds to the second semantic type,

wherein, the second pattern is different from or same as the pattern;

using the second pattern, identifying a second set of type-determined web pages;

wherein, each of the second set of type-determined web pages has content that is of the second semantic type; and

presenting, to the second user, the second set of type-determined web pages categorized as having the second semantic type;

wherein, the set of type-determined web pages are presented to the user as having the semantic type.

47. A system for optimizing search using semantics, the system comprising:

at least a processor and memory;

a URI identification module that identifies a Universal Resource Identifier (URI) of a webpage having content associated with a semantic type;

an extraction module that extracts a pattern from the URI of the webpage that is different from the URI but including a portion of the URI;

wherein, the pattern is extracted from the URI using user input;

wherein, the pattern corresponds to the semantic type,

a recognition module that performs pattern recognition, using the pattern on multiple URIs having a same domain name as the URI;

wherein, the recognition module detects URIs from the multiple URIs matching the pattern extracted from the URI;

a results generator module that identifies a set of type-determined web pages having the matching URIs;

wherein, each of the set of type-determined web pages has content that is related to the semantic type;

a data mining module that data mines the content of each of the set of type-determined web pages to further determine relevancy to the semantic type; and

a search optimizer module that identifies a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining;

wherein the extraction module further extracts a sub-pattern from the URI of the webpage having content associated with the semantic type;

wherein, the sub-pattern corresponds to an attribute of the semantic type of the content;

wherein the recognition module further performs pattern recognition on the multiple URIs and detects a subset of the URIs matching the sub-pattern;

wherein the results generator module further identifies a subset of the set of type-determined web pages having the subset of the matching URIs;

wherein, each of the subset of the type-determined web pages includes content associated with the attribute of the semantic type; and

wherein, the semantic type is associated with attributes that are user-defined.

48. The system of claim 47, further comprising:

a user interface module that presents, on a first page in a user interface, the type-determined web pages categorized as having the semantic type and links to each of the multiple subsets of the set of type-determined web pages that are associated with one of the multiple attributes of the semantic type;

wherein, each of the links is identified, on the first page, by each of the multiple attributes.