Improved Sentence Level Clustering Using Fuzzy Hierarchical With Semantic Based Algorithm

Akhila Balan, Kasim K

Abstract: Clustering is the process of grouping of the data into several categories. It is used to reveal natural structures and identify interesting patterns in the underlying data. Sentence Clustering is one of the important techniques, task of grouping a set of document so that sentence in the same group is more similar to each other than to those in other groups and it is identified based on semantic means. In this paper, an fuzzy hierarchical with semantic means clustering algorithm for sentence clustering is proposed. In this method, the text is clustered into different clusters based on hierarchical relation and also the semantic means between the sentences, which provides an effective strategy for clustering the sentence. This improves the efficiency of sentence level clustering and identifies more sentences with semantic value.

Keywords: Clustering, Expectation Maximization clustering algorithm, Fuzzy clustering algorithm,

How to Cite?: Akhila Balan, Kasim K, "Improved Sentence Level Clustering Using Fuzzy Hierarchical With Semantic Based Algorithm", Volume 4 Issue 5, May 2015, International Journal of Science and Research (IJSR), Pages: 346-349, https://www.ijsr.net/getabstract.php?paperid=SUB154123, DOI: https://dx.doi.org/10.21275/SUB154123