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Clustering web search results using fuzzy ants. (English) Zbl 1115.68021
Summary: 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.

MSC:
68M10 Network design and communication in computer systems
68P10 Searching and sorting
68T05 Learning and adaptive systems in artificial intelligence
Software:
AntClust; UCI-ml
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