Search and search optimization using a pattern of a location identifier

• US 9,607,089 B2
• Filed: 10/14/2014
• Issued: 03/28/2017
• Est. Priority Date: 04/15/2009
• Status: Active Grant

• Current Assignee: Fiver LLC
• Original Assignee: VCVC III LLC (Vulcan, Inc.)
• Inventors: Wissner, James M., Spivack, Nova
• Primary Examiner(s): Ahn, Sangwoo
• Application Number:
  US14/514,313
• Publication Number:
  US 20150032716A1
• Time in Patent Office: 896 Days
• Field of Search: None
• US Class Current: 1/1
• 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 of search, comprising:

detecting, by a computer processor, a set of Universal Resource Identifiers (URIs) where texts of the URIs match a specified pattern of characters that is not a URI, without analyzing content of a set of webpages associated with the set of URIs;

wherein the specified pattern of characters matching the set of URIs includes a domain name segment or a wildcard segment, a semantic type segment, and an attributes segment;

wherein the specified pattern corresponds to a semantic type;

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

data mining, by the computer processor, content of each of the set of web pages associated with the set of URIs to determine a degree of relevancy to the semantic type; and

identifying, by the computer processor, a subset of the set of web pages based on the degrees of relevancy to the semantic type,

wherein the set of URIs correspond to user-added content in a social network.

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

3. The method of claim 1, further comprising ranking each of the set of web pages based on the degrees of relevancy determined from the data mining.

4. The method of claim 1, wherein the semantic type is defined by an end user through tagging or annotating the web pages on a user interface.

5. 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.

18. The method of claim 1, further comprising:

extracting a sub-pattern from at least one of the URIs, wherein the sub-pattern corresponds to an attribute of the semantic type;

performing pattern recognition on the URIs using the sub-pattern;

detecting a subset of the matching URIs that match the sub-pattern; and

identifying a subset of web pages associated with the matching URIs, wherein each of the subset of web pages includes content associated with the attributed of the semantic type.

6. A system for search, comprising:

a process and memory, cooperating to function as;

a detecting unit configured to detect a set of Universal Resource Identifiers (URIs) where texts of the URIs match a specified pattern of characters that is not a URI, without analyzing content of a set of webpages associated with the set of URIs,

wherein the specified pattern corresponds to a semantic type and includes a domain name segment or a wildcard segment, a semantic type segment, and an attributes segment;

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

a mining unit configured to mine content of each of the set of web pages associated with the set of URIs to determine a degree of relevancy to the semantic type; and

an identifying unit configured to identify a subset of the set of web pages based on the degrees of relevancy to the semantic type,

wherein the set of URIs correspond to user-added content in a social network.

7. A method performed by a search engine, comprising:

detecting, by a computer processor, a set of Universal Resource Identifiers (URIs) where texts of the URIs match a specified pattern of characters that is not a URI, without analyzing content of a set of webpages associated with the set of URIs;

wherein the specified pattern corresponds to a semantic type,

wherein the specified pattern includes a domain name segment or a wildcard segment, a semantic type segment, and an attributes segment, and

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

data mining, by the computer processor, content of each of the set of web pages associated with the set of URIs to determine a degree of relevancy to the semantic type; and

identifying, by the computer processor, a subset of the set of web pages based on the degrees of relevancy to the semantic type.

8. The method of claim 7, where the multiple attributes are rated by users via a user interface.

9. The method of claim 7, wherein some of the multiple attributes are determined by a predefined ontology.

10. The method of claim 7, wherein the set of URIs correspond to user-added content in a social network.

11. The method of claim 7, wherein the set of URIs correspond to links in a sitemap.

12. The method of claim 7, wherein the semantic type is automatically determined.

13. The method of claim 7, further comprising identifying multiple patterns corresponding to the semantic type from the set of web pages.

14. The method of claim 7, wherein the specified pattern corresponds to an attribute of the semantic type.

15. The method of claim 14, wherein each of the web pages includes content that is associated with the attribute of the semantic type.

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

17. A non-transitory machine-readable storage medium having stored thereon instructions which when executed by a processor performs a method, the method comprising:

detecting a set of Universal Resource Identifiers (URIs) where texts of the URIs match a specified pattern of characters that is not a URI, without analyzing content of a set of webpages associated with the set of URIs;

wherein the specified pattern corresponds to a semantic type,

wherein the specified pattern includes a domain name segment or a wildcard segment, a semantic type segment, and an attributes segment, and

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

data mining content of each of the set of web pages associated with the set of URIs to determine a degree of relevancy to the semantic type; and

identifying a subset of the set of web pages based on the degrees of relevancy to the semantic type.