A Fuzzy Clustering Algorithm with Multi-medoids for Multi-view Relational Data

Abstract

There is an increasing interest for multi-view clustering due to its ability to manage data from several sources. The majority of multi-view clustering algorithms are suitable to analyse vector data, but much less attention has been given for the analysis of relational data. This paper provides a fuzzy clustering algorithm with multi-medoids for multi-view relational data (MFMMdd). Experiments with real multi-view data sets show the good performance of the MFMMdd in comparison with previous multi-view clustering algorithms for relational data, concerning the quality of the partitions provided by these algorithms.