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AntClust: Ant clustering and web usage mining. (English) Zbl 1028.68819
Cantú-Paz, Erick (ed.) et al., Genetic and evolutionary computation - GECCO 2003. Genetic and evolutionary computation conference, Chicago, IL, USA, July 12-16, 2003. Proceedings, Part I. Berlin: Springer. Lect. Notes Comput. Sci. 2723, 25-36 (2003).
Summary: In this paper, we propose a new ant-based clustering algorithm called AntClust. It is inspired from the chemical recognition system of ants. In this system, the continuous interactions between the nestmates generate a “Gestalt” colonial odor. Similarly, our clustering algorithm associates an object of the data set to the odor of an ant and then simulates meetings between ants. At the end, artificial ants that share a similar odor are grouped in the same nest, which provides the expected partition. We compare AntClust to the K-Means method and to the AntClass algorithm. We present new results on artificial and real data sets. We show that AntClust performs well and can extract meaningful knowledge from real Web sessions.
For the entire collection see [Zbl 1025.68696].

68U99 Computing methodologies and applications
68T05 Learning and adaptive systems in artificial intelligence
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