%0 Journal Article
	%A S.Aranganayagi and  K.Thangavel
	%D 2010
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 37, 2010
	%T Incremental Algorithm to Cluster the Categorical Data with Frequency Based Similarity Measure
	%U https://publications.waset.org/pdf/14709
	%V 37
	%X Clustering categorical data is more complicated than
the numerical clustering because of its special properties. Scalability
and memory constraint is the challenging problem in clustering large
data set. This paper presents an incremental algorithm to cluster the
categorical data. Frequencies of attribute values contribute much in
clustering similar categorical objects. In this paper we propose new
similarity measures based on the frequencies of attribute values and
its cardinalities. The proposed measures and the algorithm are
experimented with the data sets from UCI data repository. Results
prove that the proposed method generates better clusters than the
existing one.
	%P 168 - 176