Hierarchical categorization of documents is a task receiving growing interest due to the widespread proliferation of topic hierarchies for text documents. The worst problem of hie...
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
Computational resources for research in legal environments have historically implied remote access to large databases of legal documents such as case law, statutes, law reviews an...
Jack G. Conrad, Khalid Al-Kofahi, Ying Zhao, Georg...
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
Belief Propagation (BP) can be very useful and efficient for performing approximate inference on graphs. But when the graph is very highly connected with strong conflicting intera...