mented with Semantic Similarity for Text Mining Similarity for Text Mining Similarity for Text Mining Similarity for Text Mining
S. Revathi, T. Nalini · 2013
Semantic similarity is a way of analyzing the perfect synonym t hat exists between wordpairs. This measure is necessary to detect the degree of relationship that persists within wordpairs. To compute the semantic similarity that lies between a wordpair, clustering and classification augmented with semantic similarity (CCASS) was developed. CCASS is a novel method that uses page counts and text snippets returned by search engine. Several similarity measures are defined using the page counts of word� pairs. Lexical pattern clustering is applied on text snippets, obtained from search engine. These are fed to the support vector machine (SVM) which computes the semantic similarity that exists between wordpairs. Based on this value obtained from the support vector machine, Simple KMeans clustering algorithm is used to form clusters. Upcoming wordpairs can be classified, after computation of its semantic similarity measure. If it does match with the existing clusters, a new cluster may be created.