Documents and authors can be clustered into “knowledge communities” based on the overlap in the papers they cite. We introduce a new clustering algorithm, Streemer, which fin...
Vasileios Kandylas, S. Phineas Upham, Lyle H. Unga...
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
Document clustering techniques mostly rely on single term analysis of the document data set, such as the Vector Space Model. To better capture the structure of documents, the unde...
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Great e orts have been paid in the Intelligent Database Systems Research Lab for the research and development of e cient data mining methods and construction of on-line analytical...