We present in this paper a modification of Lumer and Faieta’s algorithm for data clustering. This algorithm discovers automatically clusters in numerical data without prior kno...
In this paper, a new symmetry-based genetic clustering algorithm is proposed which automatically evolves the number of clusters as well as the proper partitioning from a data set. ...
Clustering attempts to discover significant groups present in a data set. It is an unsupervised process. It is difficult to define when a clustering result is acceptable. Thus,...
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...