Most current ontology management systems concentrate on detecting usage-driven changes and representing changes formally in order to maintain the consistency. In this paper, we pr...
Majigsuren Enkhsaikhan, Wilson Wong, Wei Liu, Mark...
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
1 Multi-paradigm, multi-threaded and multi-core computing devices available today provide several orders of magnitude performance improvement over mainstream microprocessors. These...
Jeremy S. Meredith, Sadaf R. Alam, Jeffrey S. Vett...
Increasingly powerful fault management systems are required to ensure robustness and quality of service in today’s networks. In this context, event correlation is of prime impor...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...