In this paper, we present a stream-based mining algorithm for online anomaly prediction. Many real-world applications such as data stream analysis requires continuous cluster opera...
The importance of text mining stems from the availability of huge volumes of text databases holding a wealth of valuable information that needs to be mined. Text categorization is...
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
Similarity search and data mining often rely on distance or similarity functions in order to provide meaningful results and semantically meaningful patterns. However, standard dist...
Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Mat...
We are interested in finding natural communities in largescale linked networks. Our ultimate goal is to track changes over time in such communities. For such temporal tracking, we...
John E. Hopcroft, Omar Khan, Brian Kulis, Bart Sel...