Clustering For Non sentence Data Sets Using HFRECCA (Hierarchical Fuzzy Relational Eigenvector Centrality based Clustering Algorithm)
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2014, Vol 3, Issue 10
Abstract
Clustering is the process of grouping or aggregating of data items. Sentence clustering mainly used in variety of applications such as classify and categorization of documents, automatic summary generation, organizing the documents, etc. In text processing, sentence clustering plays a vital role this is used in text mining activities. Size of the clusters may change from one cluster to another. The traditional clustering algorithms have some problems in clustering the input dataset. The problems such as, instability of clusters, complexity and sensitivity. To overcome the drawbacks of these clustering algorithms, this paper proposes a algorithm called 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.
Authors and Affiliations
K. Anusha, A. K. Mahalakshmi
Keywords
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