Large, high dimensional data spaces, are still a challenge for current data clustering methods. Frequent Termset (FTS) clustering is a technique developed to cope with these chall...
Although clustering under constraints is a current research topic, a hierarchical setting, in which a hierarchy of clusters is the goal, is usually not considered. This paper trie...
This paper studies an extension of the k-median problem where we are given a metric space (V, d) and not just one but m client sets {Si V }m i=1, and the goal is to open k facili...
Barbara M. Anthony, Vineet Goyal, Anupam Gupta, Vi...
In this paper we address the issue of conceptual modeling of data used in multidimensional analysis. We view the problem from the end-user point of view and we describe a set of r...
Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality Preserving Projections (LPP). These are linear projecti...