IK-BKM: An incremental clustering approach based on intra-cluster distance

摘要

This paper introduces a novel incremental approach to clustering uncertain categorical data. This so-called Incremental K Belief K-modes Method (IK-BKM) extends the Belief K-modes one to update the cluster partition when new information is available namely the increase of final desired clusters' number. The main objective is to update clusters' partition without complete reclustring. Our method will be illustrated by an example showing the comparative results of the incremental process and the non incremental one.