Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
Correlated motif mining (CMM) is the problem to find overrepresented pairs of patterns, called motif pairs, in interacting protein sequences. Algorithmic solutions for CMM thereb...
Peter Boyen, Frank Neven, Dries Van Dyck, Aalt-Jan...
Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of oc...
Order-preserving submatrices (OPSM’s) have been shown useful in capturing concurrent patterns in data when the relative magnitudes of data items are more important than their ab...
With the huge number of information sources available on the Internet, Peer-to-Peer (P2P) systems offer a novel kind of system architecture providing the large-scale community wit...