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...
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Wedescribea novel approachfor clustering collectionsof sets,andits applicationto theanalysis and mining of categoricaldata. By "categorical data," we meantableswith fiel...
David Gibson, Jon M. Kleinberg, Prabhakar Raghavan
The goal of this work is to study the feasibility of a Heterogeneous Data Classification and Search (HDCS) system and to provide a possible design for its implementing. In order t...
Dorin Carstoiu, Alexandra Cernian, Adriana Olteanu...
We study the problem of clustering uncertain objects whose locations are described by probability density functions (pdf). We show that the UK-means algorithm, which generalises t...
Ben Kao, Sau Dan Lee, David W. Cheung, Wai-Shing H...