Semantic text clustering using enhanced vector space model using Nepali language

Abstract

The vector space model is popular method for the clustering process while doing research in the field of text mining. The main reason of its popularity is its less computational overhead and simplicity. Classical vector space model can not be used for semantic analysis purpose because it simply uses syntactic model for clustering. In order to cluster the documents in sentence level, how individual keyword plays the important roles in the text clustering, is studied in this work. For this, an Enhanced method is proposed which can easily outperform classical vector space model due to the involvement of fuzzy set approach. The classical Vector Space Model is enriched with fuzzy set so as to form the Enhanced Vector Space Model in text clustering.In order to give the semantic text clustering, fuzzy set plays crucial role in addition to classical Vector Space Model.