Incremental Affinity Spread Clustering Created on Message Passing

Abstract

Affinity propagation (AP) is a clustering method that can find data centers or clusters by sending messages between pairs of data points. Seed Affinity Propagation is a novel semi supervised text clustering algorithm which is based on AP. AP algorithm couldn’t cope up with part known data direct. Therefore, focusing on this issue a semi-supervised scheme called incremental affinity propagation clustering is present in the paper where pre-known information is represented by adjusting similarity matrix The standard affinity propagation clustering algorithm also suffers from a limitation that it is hard to know the value of the parameter “preference” which can yield an optimal clustering solution. This limitation can be overcome by a method named, adaptive affinity propagation. The method first finds out the range of “preference”, then searches the space of “preference” to find a good value which can optimize the clustering result.