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Genetic operators for hierarchical graph clustering
Authors:Stefano Rizzi
Affiliation:DEIS, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy
Abstract:
In this paper we propose an encoding scheme and ad hoc operators for a genetic approach to hierarchical graph clustering. Given a connected graph whose vertices correspond to points within a Euclidean space and a fitness function, a hierarchy of graphs in which each vertex corresponds to a connected subgraph of the graph below is generated. Both the number of clustering levels and the number of clusters on each level are not fixed a priori and are subject to optimization.
Keywords:Hierarchical clustering   Genetic algorithms   Autonomous robots   Euclidean graphs
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