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 present several methods for mining knowledge from the query logs of the MSN search engine. Using the query logs, we build a time series for each query word or phrase (e.g., `Th...
Michail Vlachos, Christopher Meek, Zografoula Vage...
Besides the problem of searching for effective methods for extracting knowledge from large databases (KDD) there are some additional problems with handling ecological data, namely ...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Wireless sensor networks (WSNs) represent a typical domain where there are complex temporal sequences of events. In this paper we propose a relational framework to model and analys...
Teresa Maria Altomare Basile, Nicola Di Mauro, Ste...