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Clustering web search results using fuzzy ants

โœ Scribed by Steven Schockaert; Martine De Cock; Chris Cornelis; Etienne E. Kerre

Publisher
John Wiley and Sons
Year
2007
Tongue
English
Weight
237 KB
Volume
22
Category
Article
ISSN
0884-8173

No coin nor oath required. For personal study only.

โœฆ Synopsis

Algorithms for clustering Web search results have to be efficient and robust. Furthermore they must be able to cluster a data set without using any kind of a priori information, such as the required number of clusters. Clustering algorithms inspired by the behavior of real ants generally meet these requirements. In this article we propose a novel approach to ant-based clustering, based on fuzzy logic. We show that it improves existing approaches and illustrates how our algorithm can be applied to the problem of Web search results clustering.

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