  As the amount of online text increases, the demand for text categorization 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 categorization 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. Text
categorization using Association Rule and Na\"ive Bayes Classifier is proposed
here. Instead of using words word relation i.e association rules from these
words is used to derive feature set from pre-classified text documents. Naive
Bayes Classifier is then used on derived features for final categorization.

Information Retrieval;Databases