A New Clustering Technique On Text In Sentence For Text Mining

Clustering is a commonly considered data mining problem in the text domains. The problem finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In this paper, the sentence level based clustering algorithm is discussed as a survey. The survey explains about the problems in clustering in sentence level and the solutions to overcome these problems. This paper presents a novel fuzzy clustering algorithm that operates on relational input data; i.e., data in the form of a square matrix of pairwise similarities between data objects Hierarchical Fuzzy Relational Eigenvector Centrality-based Clustering Algorithm (HFRECCA) is extension of FRECCA which is used for the clustering of sentences. Contents present in text documents contain hierarchical structure and there are many terms present in the documents which are related to more than one theme hence HFRECCA will be useful algorithm for natural language documents. In this algorithm single object may belong to more than one cluster.