Graph-structured data is becoming increasingly abundant in many application domains. Graph mining aims at finding interesting patterns within this data that represent novel knowl...
Karsten M. Borgwardt, Hans-Peter Kriegel, Peter Wa...
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
Constraint-based mining has been proven to be extremely useful for supporting actionable pattern discovery. However, useful conjunctions of constraints that support domain driven ...
We empirically evaluate the performance of various reinforcement learning methods in applications to sequential targeted marketing. In particular, we propose and evaluate a progre...
Naoki Abe, Edwin P. D. Pednault, Haixun Wang, Bian...
Association rules mining is a frequently used technique which finds interesting association and correlation relationships among large set of data items which occur frequently toge...