Research Of Text Mining And Application In Topic Search

Text mining is a process of mining the valuable information in text data. With the rapid development of network technology, the Internet has become a major carrier of information. People have been getting used to scan theme related information page through the search engine. But users may not browse all the search results from search engines, just need to be browsed the basic summary information of the web pages. In this way, the search engines will need to text mining technology to extract information from web page. Therefore, WEB text mining is becoming a hot point of the research of text mining, but also be an indispensable part of search engine.In this paper, the text mining research mainly includes three aspects:extracting the text information from WEB page based on Document Object Model, changing the WEB text mining into the traditional text mining; the research and implementation of the text classification system, to verify the many kinds of feature selection ways and the improvement of MI feature selection; the research and implementation of the text clustering process, proving the availability of natural language processing technology in text clustering feature selection.Then, this paper analyzes the topic search engine’s text mining demand, uses information extraction technology, text classification technology and text clustering technology to design and implement the topic search engine’s text mining module.In this paper, those designed, implemented and researched technologies have practice application meaning.