Most clustering algorithms are partitional in nature, assigning each data point to exactly one cluster. However, several real world datasets have inherently overlapping clusters i...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
In this paper, we propose a new similarity measure to compute the pairwise similarity of text-based documents based on suffix tree document model. By applying the new suffix tree ...
This paper deals with clustering of spatially distributed data using wireless sensor networks. A distributed low-complexity clustering algorithm is developed that requires one-hop...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...
In this paper we study simple families of clustered graphs that are highly unconnected. We start by studying 3-cluster cycles, which are clustered graphs such that the underlying ...
Pier Francesco Cortese, Giuseppe Di Battista, Maur...