In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Biosequences typically have a small alphabet, a long length, and patterns containing gaps (i.e., “don’t care”) of arbitrary size. Mining frequent patterns in such sequences ...
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
The problem of mining spatiotemporal patterns is finding sequences of events that occur frequently in spatiotemporal datasets. Spatiotemporal datasets store the evolution of object...
Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...