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We have presented in this paper an ants based clustering algorithm which is inspired from the self-assembling behavior observed in real ants. These ants progressively become connected to an initial point called the support and then successively to other connected ants. The artificial ants that we have defined similarly build a tree where each ant represents a node/data. Ants use the similarities between...
We present in this paper a new clustering method which provides self-organization of hierarchical clustering. This method represents large datasets on a forest of original trees which are projected on a simple 2D geometric relationship using tree map representation. The obtained partition is represented by a map of tree maps, which define a tree of data. In this paper, we provide the rules that build...
In this paper we present a new incremental algorithm for building neighborhood graphs between data. It is inspired from the self-assembly behavior observed in real ants where ants progressively become attached to an existing support and then successively to other attached ants. Each artificial ant represents one data. The way ants move and build a graph depends on the similarity between the data....
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