Previous studies on mining sequential patterns have focused on temporal patterns specified by some form of propositional temporal logic. However, there are some interesting seque...
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
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...
Both, the number and the size of spatial databases, such as geographic or medical databases, are rapidly growing because of the large amount of data obtained from satellite images,...