Automated adversarial detection systems can fail when under attack by adversaries. As part of a resilient data stream mining system to reduce the possibility of such failure, adap...
Clifton Phua, Kate Smith-Miles, Vincent C. S. Lee,...
Periodicy detection in time series data is a challenging problem of great importance in many applications. Most previous work focused on mining synchronous periodic patterns and d...
The focus of this paper is to develop algorithms and a framework for modeling transactional data stored in relational database into graphs for mining. Most of the real-world trans...
We investigate the problem of mining closed sets in multi-relational databases. Previous work introduced different semantics and associated algorithms for mining closed sets in mu...
Abstract. Recent results on robust density-based clustering have indicated that the uncertainty associated with the actual measurements can be exploited to locate objects that are ...