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Optimal sentence clustering for web database using hierarchical fuzzy relational clustering integrated with artificial bee colony algorithm

Author

Listed:
  • Santhi Venkatraman
  • R. Prasanthini

Abstract

Sentence clustering plays a vital role in text mining and text processing activities. The proposed work is a novel hierarchical fuzzy relational clustering algorithm (HFRECA) capable of identifying sub clusters. It has features of both hierarchical clustering and fuzzy clustering in which it uses page rank to form multiple clusters present in text documents containing hierarchical structure. To enhance the quality of the clusters formed, an optimisation algorithm which is called artificial bee colony (ABC) algorithm is used along with it. The proposed algorithm identifies the sub clusters and finely tunes the cluster to show a better optimised result.

Suggested Citation

  • Santhi Venkatraman & R. Prasanthini, 2018. "Optimal sentence clustering for web database using hierarchical fuzzy relational clustering integrated with artificial bee colony algorithm," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 27(3), pages 367-382.
    • Handle: RePEc:ids:ijbisy:v:27:y:2018:i:3:p:367-382
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