Search and search optimization using a pattern of a location identifier

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.

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.

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.