Automatic Text Categorization on News Articles

Text categorization is a term that has intrigued researchers for quite some time now. It is the concept in which news articles are categorized into specific groups to cut down efforts put in manually categorizing news articles into particular groups. A growing number of statistical classification and machine learning technique have been applied to text categorization. This paper is based on the automatic text categorization of news articles based on clustering using k-mean algorithm. The goal of this paper is to automatically categorize news articles into groups. Our paper mostly concentrates on K-mean for clustering and for term frequency we are going to use TF-IDF dictionary is applied for categorization. This is done using mahaout as platform.