In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Constrained pattern mining extracts patterns based on their individual merit. Usually this results in far more patterns than a human expert or a machine learning technique could m...
Discovery of sequential patterns is becoming increasingly useful and essential in many scienti c and commercial domains. Enormous sizes of available datasets and possibly large nu...
Discovering frequent patterns from huge amounts of data is one of the most studied problems in data mining. However, some sensitive patterns with security policies may cause a thr...