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IJIS
2007

Clustering web search results using fuzzy ants

9 years 11 months ago
Clustering web search results using fuzzy ants
Algorithms for clustering web search results have to be efficient and robust. Furthermore they must be able to cluster a dataset without using any kind of a priori information, such as the required number of clusters. Clustering algorithms inspired by the behaviour of real ants generally meet these requirements. In this paper we propose a novel approach to ant based clustering, based on fuzzy logic. We show that it improves existing approaches and illustrate how our algorithm can be applied to the problem of web search results clustering.
Steven Schockaert, Martine De Cock, Chris Cornelis
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2007
Where IJIS
Authors Steven Schockaert, Martine De Cock, Chris Cornelis, Etienne E. Kerre
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