Summarization of sentences using fuzzy and hierarchical clustering approach

Abstract

The process of grouping or combining of data items known as clustering and groups formed are clusters. Sentence clustering mainly utilized in variety of applications such as grouping, categorization of documents, automatic summary generation, organization of the documents etc. Sentence clustering has importance in the text mining domain. Cluster sizes vary from one another. There are some problems in traditional clustering such as instability of clusters, complexity and sensitivity. In this paper we have implemented a Hierarchical and Fuzzy Relational Eigenvector Centrality-based Clustering Algorithm for the clustering of sentences to overcome the problems of traditional clustering methods. The experimental result shows that Hierarchical clustering will be useful algorithm for text documents and gives better results.