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13

ADMA
2007
Springer

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Topic Extraction with AGAPE

13 years 10 months ago

Topic Extraction with AGAPE

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This paper uses an optimization approach to address the problem of conceptual clustering. The aim of AGAPE, which is based on the tabu-search meta-heuristic using split, merge and a special “k-means” move, is to extract concepts by optimizing a global quality function. It is deterministic and uses no a priori knowledge about the number of clusters. Experiments carried out in topic extraction show very promising results on both artiﬁcial and real datasets.

Julien Velcin, Jean-Gabriel Ganascia

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ADMA 2007 | Conceptual Clustering | Data Mining | Global Quality Function | Optimization Approach |

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Added	06 Jun 2010
Updated	06 Jun 2010
Type	Conference
Year	2007
Where	ADMA
Authors	Julien Velcin, Jean-Gabriel Ganascia

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