Text classification using the concepts of data mining association rules

Rahman, C.M., Sohel, F.A., Naushad, P. and Kamruzzaman, S.M. (2003) Text classification using the concepts of data mining association rules. In: International Conference on Information Technology: Prospects and Challenges in the 21st century, May 2003, Kathmandu, Nepal

Abstract

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. Naïve Bayes classifier is then used on derived features for final classification.

Item Type:	Conference Paper
URI:	http://researchrepository.murdoch.edu.au/id/eprint/28575

Item Control Page

Downloads