In this paper, we present a framework for mining diverging patterns, a new type of contrast patterns whose frequency changes significantly differently in two data sets, e.g., it c...
In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbase...
With ever-increasing amounts of graph data from disparate sources, there has been a strong need for exploiting significant graph patterns with user-specified objective functions. ...
In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...
Existing temporal pattern mining assumes that events do not have any duration. However, events in many real world applications have durations, and the relationships among these ev...