Web Text Mining through Machine Learning for Information Classification and Pattern Analysis: A Review


  • M. Venugopal
  • Dr. V. K. Sharma
  • Dr. Kalpana Sharma


In current years, there is tremendous development in information sharing and distribution on the web. In such the text data contributes the largest repositories. The main source of text data prominently comes from various information publications in multiple domains and social networks. Mining of such high volume of distributed information needs appropriate classification of the information. Due to which the mechanism of data mining is rapidly being utilizedto mine this various information to make it available for the application needs through web text mining (WTM) mechanism. However, WTMis facing many challenges to classify this information accurately due to the diversity of the information due to its context and semantic meaning. This paper aims to reviews the WTM andMachine Learning techniques to enhance the information classification through knowledge the various pattern analysis and its challenges. It intends to briefly review the importance of information classification in the field of Web text applications, especially for enterprise and social applications, and also to review existing techniques and methods for addressing the issue of extracting information from Web sources.