We define a cluster to be characterized by regions of high density separated by regions that are sparse. By observing the downward closure property of density, the search for inte...
Alexei D. Miasnikov, Jayson E. Rome, Robert M. Har...
The diameter k-clustering problem is the problem of partitioning a finite subset of Rd into k subsets called clusters such that the maximum diameter of the clusters is minimized. ...
Document clustering has been used for better document retrieval, document browsing, and text mining in digital library. In this paper, we perform a comprehensive comparison study ...
We present a novel algorithm called CLICKS, that finds clusters in categorical datasets based on a search for kpartite maximal cliques. Unlike previous methods, CLICKS mines subs...
A new approach has been developed for acquiring bilingual web pages from the result pages of search engines, which is composed of two challenging tasks. The first task is to detec...