Topic Extraction with AGAPE

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.

• Type: Conference
• Year: 2007
• Where: ADMA
• Authors: Julien Velcin, Jean-Gabriel Ganascia
• Keywords: ADMA 2007, Conceptual Clustering, Data Mining, Global Quality Function, Optimization Approach