Towards a Suitable Reconciliation of the Findings in Collaborative Fuzzy Clustering

Abstract

This study is concerned with the application of multi-objective particle swarm optimization (MOPSO) approaches to the framework of collaborative fuzzy clustering. In particular, the emphasis lies in determining the collaboration matrix between the data repositories. By using fitness functions both at the level of data and information granules, we can provide a more effective way of reconciling the findings between the participating data sites. A practical application of the proposed methodology to marketing research is presented.