An affinity propagation algorithm embedded in Optimizable Dissimilarity Measure

It gives an Affinity Propagation Clustering algorithm embedded in Optimizable Dissimilarity Measure(APCODM), in order to find a more meaningful clustering distribution by searching a better dissimilarity measure in hybrid attributes data space. After some necessary discuss, it gives its time complexity and astringency analysis. The APCODM can some time get a better clustering quality validated by experiments of several data sets. At last, it indicates several valuable research expectations.