Method for categorizing content published on internet

• US 7,945,555 B2
• Filed: 12/27/2007
• Issued: 05/17/2011
• Est. Priority Date: 02/01/2007
• Status: Expired due to Fees

• Current Assignee: YUME Incorporated (Nexxen International Ltd.)
• Original Assignee: YUME Incorporated (Nexxen International Ltd.)
• Inventors: Sankaran, Ayyappan, Kadambi, Jayant, Shaver, Matthew D
• Primary Examiner(s): Trujillo; James
• Assistant Examiner(s): Moser; Bruce M
• Application Number:
  US11/964,711
• Publication Number:
  US 20080189307A1
• Time in Patent Office: 1,237 Days
• Field of Search: 707/100, 707/999.1, 707/710, 707/739, 707/740, 707/748, 705/10, 705/14, 705/14.52
• US Class Current: 707/710
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06Q 30/0254 based on statistics

Abstract

The present invention provides method and system for categorizing a content published on Internet. The method comprising gathering one or more feeds associated with the content. The method further comprises extracting contextual information from the one or more feeds. Thereafter, the content is categorized into one or more general web-based categories belonging to a set of general web-based categories. The categorizing step further comprises performing a semantic analysis of the contextual information that yields a keyword string. The content is classified into the one or more general web-based category based on the keyword string. Finally, the set of general web-based categories is translated to a set of pre-defined categories, such that one or more general web-based category is translated to a pre-defined category that is relevant to an end user.

Claims

1. A method for categorizing at least one content on Internet, the method comprising:

gathering one or more feeds associated with the at least one content, wherein the at least one content is provided by at least one content provider;

extracting contextual information from the one or more feeds, wherein the contextual information is embedded into the one or more feeds;

categorizing the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, the categorizing step comprising;

performing a semantic analysis of the contextual information,

wherein the semantic analysis of the contextual information yields a keyword string corresponding to the contextual information; and

classifying the at least one content into the at least one general web-based category based on the keyword string;

translating the set of general web-based categories to a set of pre-defined categories, wherein one or more general web-based categories from the set of general web-based categories are translated to at least one pre-defined category in the set of pre-defined categories, wherein the at least one content belongs to at least one pre-defined category when translating the set of general web-based categories to the set of pre-defined categories;

wherein the categorizing step further comprises computing a first relevance percentage corresponding to the at least one content classified into each of the at least one general web-based category.

2. The method of claim 1, wherein the translating step comprises determining a set of associations between the set of general web-based categories and the set of pre-defined categories, wherein an association from the set of associations maps a general web-based category and one or more sub-categories of the general web-based category with a pre-defined category, wherein the association is determined based on a relationship between a first string pattern and a second string pattern, wherein the first string pattern corresponds to the general web-based category and the one or more sub-categories of the general web-based category and the second string pattern corresponds to the pre-defined category.

3. The method of claim 1, wherein the translating step comprises computing a second relevance percentage corresponding to the at least one content belonging to each of the at least one pre-defined category.

4. The method of claim 1, wherein the translating step comprises a manual translation of one or more general web-based categories to one or more pre-defined categories when a translation of the one or more general web-based categories to each pre-defined category in the set of pre-defined categories is absent.

5. The method of claim 1, wherein the translating step comprises translating one or more general web-based categories to a miscellaneous category when a translation of the one or more general web-based categories to each pre-defined category in the set of pre-defined categories is absent, the miscellaneous category belonging to the set of pre-defined categories.

6. The method of claim 1, wherein the gathering step comprises at least one of polling the at least one content provider for at least one new feed and automatically receiving the at least one new feed from the at least one content provider.

7. The method of claim 1, wherein the set of general web-based categories is represented using a first hierarchical structure and the set of pre-defined categories is represented using a second hierarchical structure, the second hierarchical structure comprising at most a predetermined number of levels.

8. The method of claim 1, wherein a general web-based categorizing engine categorizes the at least one content into at least one general web-based category.

9. The method of claim 1, wherein the one or more feeds are obtained in at least one of a RSS 2.0 format and an ATOM 1.0 format.

10. The method of claim 1, wherein the contextual information is at least one of a content tag and a content catalogue information corresponding to the at least one content.

11. The method of claim 1, wherein the set of general web-based categories is at least one of a set of Open Directory (dmoz) categories and a set of Yahoo directory categories.

12. A computing system for categorizing at least one content on Internet, the computing system comprising:

a processor implemented gathering module, the processor implemented gathering module gathering one or more feeds associated with the at least one content, the at least one content provided by at least one content provider;

a processor implemented extracting module, the processor implemented extracting module extracting contextual information from the one or more feeds, wherein the contextual information is embedded into the one or more feeds;

a processor implemented categorizing module, the processor implemented categorizing module categorizing the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, the processor implemented categorizing module comprising;

a processor implemented analyzing module, the processor implemented analyzing module performing a semantic analysis of the contextual information, wherein the semantic analysis of the contextual information yields a keyword string corresponding to the contextual information; and

a processor implemented classifying module, the processor implemented classifying module classifying the at least one content into the at least one general web-based category based on the keyword string; and

a processor implemented translating module, the processor implemented translating module translating the set of general web-based categories to a set of pre-defined categories, wherein one or more general web-based categories from the set of general web-based categories are translated to at least one pre-defined category in the set of pre-defined categories, wherein the at least one content belongs to at least one pre-defined category when translating the set of general web-based categories to the set of pre-defined categories; and

wherein the categorizing module further comprises a first computing module, the first computing module computing a first relevance percentage corresponding to the at least one content classified into each of the at least one general web-based category.

13. The system of claim 12, wherein the processor implemented translating module is configured for determining a set of associations between the set of general web-based categories and the set of pre-defined categories, wherein an association from the set of associations connects a general web-based category and one or more sub-categories of the general web-based category with a pre-defined category, wherein the association is determined based on a relationship between a first string pattern and a second string pattern, wherein the first string pattern corresponds to the general web-based category and the one or more sub-categories of the general web-based category and the second string pattern corresponds to the pre-defined category.

14. The system of claim 12, wherein the processor implemented translating module comprises a second percentage corresponding to the at least one content belonging to each of the at least one pre-defined category.

15. The system of claim 12, wherein the processor implemented translating module is configured for translating one or more general web-based categories to a miscellaneous category when a translation of the one or more general web-based categories to each pre-defined category in the set of pre-defined categories is absent, the miscellaneous category belonging to the set of pre-defined categories.

16. The system of claim 12, wherein the processor implemented translating module is configured for generating one or more new pre-defined categories in the set of pre-defined categories when a number of entries in a pre-defined category is more than a threshold number.

17. A computer program product comprising a computer usable medium having a computer readable program for categorizing at least one content on Internet, wherein the computer readable program when executed on a computer causes the computer to:

gather one or more feeds associated with the at least one content, wherein the at least one content is provided by at least one content provider;

extract contextual information from the one or more feeds, wherein the contextual information is embedded into the one or more feeds;

categorize the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, the computer readable program further causes the computer to;

perform a semantic analysis of the contextual information, wherein the semantic analysis of the contextual information yields a keyword string corresponding to the contextual information; and

classify the at least one content into the at least one general web-based category based on the keyword string;

translate the set of general web-based categories to a set of pre-defined

categories, wherein one or more general web-based categories from the set of general web-based categories are translated to at least one pre-defined category in the set of pre-defined categories, wherein the at least one content belongs to at least one pre-defined category when translating the set of general web-based categories to the set of pre-defined categories;

wherein the computer readable program when executed on the computer further causes the computer to;

compute a first relevance percentage corresponding to the at least one content classified into each of the at least one general web-based category; and

compute a second relevance percentage corresponding to the at least one content belonging to each of the at least one pre-defined category.