Analysis of Query Dependent Summarization Using Clustering Techniques

Web is playing a vital role as a resource of information. One can upload, download, access the data from web for decision making to get data query independent technique is already developed. But to have the proper data one has to go for query dependent summarization. As many documents are having similarity in them we can use clustering of the document to reduce mapping of the query with the available document. The current research work focuses on analysis of document summarization using clustering technique. The aim of our research work is to combine both approaches that is Query dependent text document summarization and Clustering algorithm. This mainly includes applying different clustering algorithms on a text document. Create a weighted document graph of the resulting graph based on the keywords. And obtain the document graph to get the summary of the document. The performance of the summary using different clustering techniques will be analyzed and the optimal approach will be suggested.