Microarray datasets are often too large to visualise due to the high dimensionality. The self-organising map has been found useful to analyse massive complex datasets. It can be us...
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...
The assessment of the reliability of clusters discovered in bio-molecular data is a central issue in several bioinformatics problems. Several methods based on the concept of stabil...
Search results clustering problem is defined as an automatic, on-line grouping of similar documents in a search hits list, returned from a search engine. In this paper we present t...
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...