Topological hierarchical tree using artificial ants

Authors:
Mustapha Lebbah;Hanane Azzag
Affiliations:
LIPN-UMR, Universit Paris 13, CNRS, Villetaneuse;LIPN-UMR, Universit Paris 13, CNRS, Villetaneuse
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Year:
2010

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Abstract

We propose in this paper a new approach for topological hierarchical tree clustering inspired from self-assembly behavior of artificial ants. Our method called THT (Topologial Hierarchical Tree) builds, autonomously and simultaneously, a topological and hierarchical partitioning of data. Each "cluster" associated to one cell of a 2D grid is modeled by a tree. The artificial ants that we define dissimilarly build a tree where each ant represents a node/data. The benefit of this novel approach is the intuitive representation of hierarchical relations in the data. This is especially appealing in explorative data mining applications, allowing the inherent structure of the data unfold in highly intuitive fashion.