Size and complexity of data repositories collaboratively created by Web users generate a need for new processing approaches. In this paper, we study the problem of detection of ï¬...
Both document clustering and word clustering are well studied problems. Most existing algorithms cluster documents and words separately but not simultaneously. In this paper we pr...
Population based real-life datasets often contain smaller clusters of unusual sub-populations. While these clusters, called `hot spots', are small and sparse, they are usuall...
We study the online clustering problem where data items arrive in an online fashion. The algorithm maintains a clustering of data items into similarity classes. Upon arrival of v, ...
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...