On the performance of bisecting K - means and PDDP * Sergio

problem is known as bisecting divisive clustering. Note that by recursively using a divisive bisecting clustering procedure, the dataset can be partitioned into any given number of clusters. Interestingly enough, the clusters so-obtained are structured as a hierarchical binary tree (or a binary taxonomy). This is the reason why the bisecting divisive approach is very attractive in many applications (e.g. in document-retrieval/indexing problems – see e.g. [17] and references cited therein). Among the divisive clustering algorithms which have been proposed in the literature in the last two decades ([13]), in this paper we will focus on two techniques: • the bisecting K-means algorithm; • the Principal Direction Divisive Partitioning (PDDP) algorithm.