An incremental clustering algorithm based on compact sets with radius α

Authors:
Aurora Pons-Porrata;Guillermo Sánchez Díaz;Manuel Lazo Cortés;Leydis Alfonso Ramírez
Affiliations:
Center of Pattern Recognition and Data Mining, University of Oriente, Santiago de Cuba, Cuba;Center of Technologies Research on Information and Systems, UAEH, Pachuca, Hgo, Mexico;Institute of Cybernetics, Mathematics and Physics, Havana, Cuba;Center of Pattern Recognition and Data Mining, University of Oriente, Santiago de Cuba, Cuba
Venue:
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2005

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Abstract

In this paper, we present an incremental clustering algorithm in the logical combinatorial approach to pattern recognition, which finds incrementally the β0-compact sets with radius α of an object collection. The proposed algorithm allows generating an intermediate subset of clusters between the β0-connected components and β0-compact sets (including both of them as particular cases). The evaluation experiments on standard document collections show that the proposed algorithm outperforms the algorithms that obtain the β0-connected components and the β0-compact sets.