Query based Text Document Clustering using its Hypernymy Relation

of text can be organized in an unsupervised manner. In this paper, Text document clustering is done based on query and its semantic relation. The method utilizes hypernymy to identify its relation. It was detected by using the Word Net. It act as background knowledge of the Query and provides its synonymic terms. This paper proposed the new term-document matrix called Query based document vector model, which is constructed using query with two terms and its hypernymy. The results show that our new measure Cluster Accuracy is significantly better to evaluate the quality of cluster and better results are obtained. General Terms Text mining and Information Retrieval, Partitioning M ethod KeywordsNoun, Word net, Query based document vector model, Hypernymy, Accuracy.

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