A novel clustering algorithm based on weighted support and its application

In this paper, we present a novel and efficient algorithm, WeiSC, for clustering categorical data, which is not only accurate but also displays good scalability. It is mainly based on weighted support, which, as defined by us, calculates the similarity between a new tuple and existing clusters. The new tuple is assigned to the cluster with largest similarity. As an example, we apply this algorithm in IDS and perform some research.