Abstract: Now a days managing a vast number of documents in digital forms is very important in text mining applications. Text categorization is a task of automatically sorting a set of documents into categories from a predefined set. A major characteristic or difficulty of text categorization is high dimensionality of feature space. The reduction of dimensionality by selecting new attributes which is subset of old attributes is known as feature selection. Feature-selection methods are discussed in this paper for reducing the dimensionality of the dataset by removing features that are considered irrelevant for the classification. In this paper we discuss several approaches of text categorization, feature selection methods and applications of text categorization.

Keywords: Text categorization, Clustering, Nave Bayes, K Nearest Neighbor, Support Vector Machine. .