The large amount of patterns generated by frequent pattern mining algorithms has been extensively addressed in the last few years. In geographic pattern mining, besides the large ...
A complete set of frequent itemsets can get undesirably large due to redundancy when the minimum support threshold is low or when the database is dense. Several concise representat...
The problem of mining spatiotemporal patterns is finding sequences of events that occur frequently in spatiotemporal datasets. Spatiotemporal datasets store the evolution of object...
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Existing sequence mining algorithms mostly focus on mining for subsequences. However, a large class of applications, such as biological DNA and protein motif mining, require effici...