An efficient three-way clustering algorithm based on gravitational search

Abstract

There are three types of relationships between an object and a cluster, namely, belong-to definitely, uncertain and not belong-to definitely. Most of the existing clustering algorithms represent a cluster with a single set and they are the two-way clustering algorithms since they just reflect two relationships. By contrast, the three-way clustering can reflect intuitively the three types of relationships with a pair of sets. However, the three-way clustering algorithms usually need to know the thresholds in advance in order to obtain the three types of relationships. To address the problem, we propose an efficient three-way clustering algorithm based on the idea of universal gravitation in this paper. The proposed method can adjust the thresholds automatically in the process of clustering and obtain more detailed ascription relation between objects and clusters. Furthermore, to guarantee the integrity of the work, we also put forward a two-way clustering algorithm to obtain the conventional two-way result. The experimental results show that the proposed algorithm is not only effective to obtain the three-way clustering result from the two-way clustering result automatically, but also it is in a better performance at the accuracy, F-measure, NMI and RI than the compared algorithms in most cases.