Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
Abstract. We are designing new data mining techniques on gene expression data, more precisely inductive querying techniques that extract a priori interesting bi-sets, i.e., sets of...
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...