AN EFFICIENT TEXT CLUSTERING ALGORITHM USING AFFINITY PROPAGATION

The objective is to find among all partitions of the data set, best publishing according to some quality measure. Affinity propagation is a low error, high speed, flexible, and remarkably simple clustering algorithm that may be used in forming teams of participants for business simulations and experiential exercises, and in organizingparticipants preferences for the parameters of simulations.This paper proposes an efficient Affinity Propagation algorithm that guaranteesthe same clustering result as the original algorithm after convergence. The heart of our approach is (1) to prune unnecessary message exchanges in the iterations and (2) to compute the convergencevalues of pruned messages after the iterations to determine clusters.