Frequent term based text document clustering using similarity measures: A novel approach

Abstract

Clustering is one of the epic and traditional ways to make sure that the documents are retrieved at the right pace and according to the requirement. Clustering leads to keeping the similar kind of documents all together and so that they can be retrieved easily. The measure through which the relation between two documents is measured is called similarity index. There are several kind of similarity index already in the process. The proposed algorithm uses two kind of similarity index and combines them to produce a new similarity index. Similarity index plays a vital role in the clustering and classification procedure. The proposed algorithm also uses Fuzzy logic for the clustering rules and furthermore it is classified by the Support Vector Machine to justify the accuracy of the proposed solution.