Spatial data mining, i.e., discovery of interesting characteristics and patterns that may implicitly exist in spatial databases, is a challenging task due to the huge amounts of s...
The increasing interest in time series data mining has had surprisingly little impact on real world medical applications. Practitioners who work with time series on a daily basis ...
Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamon...
In this paper, data mining techniques are used to analyze data gathered from online poker. The study focuses on short-handed Texas Hold'em, and the data sets used contain thou...
Classification of time series has been attracting great interest over the past decade. Recent empirical evidence has strongly suggested that the simple nearest neighbor algorithm ...
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,...