  As the amount of online text increases, the demand for text classification to
aid the analysis and management of text is increasing. Text is cheap, but
information, in the form of knowing what classes a text belongs to, is
expensive. Automatic classification of text can provide this information at low
cost, but the classifiers themselves must be built with expensive human effort,
or trained from texts which have themselves been manually classified. In this
paper we will discuss a procedure of classifying text using the concept of
association rule of data mining. Association rule mining technique has been
used to derive feature set from pre-classified text documents. Naive Bayes
classifier is then used on derived features for final classification.
