An integrated approach and framework for document clustering using graph based association rule mining

Abstract

Growth in number of documents increases day by day, and for managing this growth the document clustering techniques are used document clustering is a significant tool to allocating web search engines for data mining and knowledge discovery. In this paper, we have introduced a new framework graph-based frequent Term set for document clustering (GBFTDC). In this study, document clustering has been performed for extraction of useful information from document dataset based on frequent term set.We have generated association rules to perform pre-processing and then have applied clustering approach.