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A Critique Survey on Diverse Approaches of Web Content Mining


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1 School of CSA, REVA University, India
 

Web mining is used to find the different patterns in data by various categories like web usage mining, web structure mining and web content mining. The method used to gather data by web spiders and web search engines are known as web content mining. The formation of a website can be tartan by using web structure mining and we can test the data of a user’s browser by using web usage mining. The web content mining is a second phase of web mining, which deals with extraction of images, graphs, text etc. The spotlight of this work is to present a brief survey on different techniques used in web content mining. We presented a brief review of different web content mining approaches like multimedia mining, unstructured mining, structured mining and semi-structured mining.

Keywords

Web Mining, Web Content Mining, Multimedia Mining, Web Crawlers, Summarization, Information Extraction.
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  • A Critique Survey on Diverse Approaches of Web Content Mining

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Authors

P. V. Varish
School of CSA, REVA University, India
C. K. Lokesh
School of CSA, REVA University, India
Kavitha
School of CSA, REVA University, India

Abstract


Web mining is used to find the different patterns in data by various categories like web usage mining, web structure mining and web content mining. The method used to gather data by web spiders and web search engines are known as web content mining. The formation of a website can be tartan by using web structure mining and we can test the data of a user’s browser by using web usage mining. The web content mining is a second phase of web mining, which deals with extraction of images, graphs, text etc. The spotlight of this work is to present a brief survey on different techniques used in web content mining. We presented a brief review of different web content mining approaches like multimedia mining, unstructured mining, structured mining and semi-structured mining.

Keywords


Web Mining, Web Content Mining, Multimedia Mining, Web Crawlers, Summarization, Information Extraction.

References