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...
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
One promising application of sensor networks is object tracking. Because the movements of the tracked objects usually show repeating patterns, we propose a heterogeneous tracking ...
Abstract. In this paper, we present a theoretical foundation for querying inductive databases, which can accommodate disparate mining tasks. We present a data mining algebra includ...