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...
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,...
Knowledge discovery allows considerable insight into data. This brings with it the inherent risk that what is inferred may be private or ethically sensitive. The process of genera...
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 usage of descriptive data mining methods for predictive purposes is a recent trend in data mining research. It is well motivated by the understandability of learned models, the...