Classification of News and Research Articles Using Text Pattern Mining

Text mining is nothing but the discovery of interesting knowledge in text documents. But there is a big challenging issue that how to guarantee the quality of discovered relevant features. And that are in the text documents for describing user preferences because of the large number of terms, patterns and noise. For text mining there are basically two types of approaches; one is term based approach and another is phrase based approach. But term based approach suffered with the problem of polysemy and synonymy. And phrase based approach suffered with low frequency occurrence. But phrase based approaches are better than the term based approaches. But pattern based approach is better than the term based and phrase based approach. The proposed method utilize pattern approach with the set of keywords, which is an innovative and effective pattern discovery technique by which research articles, news articles classification of different field are done and more than 80 percent of documents are successfully identified.