Review on Sentence-Level Clustering Using Fuzzy Relational Clustering Algorithm

Clustering is a widely studied data mining problem in the text domains. In text processing, clustering the sentence is one of the processes and used within general text mining tasks. Many clustering methods and algorithms are used for clustering the documents at sentence level. In this paper, the sentence level based clustering algorithm is discussed. It is explained that there are the no. of problems in clustering in sentence level and the solutions to overcome these problems. It is related with soft clustering. As in hard clustering methods, pattern belongs to a single cluster, means objects similar to each other are placed in one cluster where dissimilar objects are placed into another one. But fuzzy clustering algorithms allow patterns to belong to all clusters with differing degrees of membership. This is important in case of sentence clustering, since a sentence is likely to be related to more than one theme or topic present within a document or set of documents. 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 pair wise similarities between data objects. After, clustering optimized using different algorithms.