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...
Frequent embedded subtree pattern mining is an important data mining problem with broad applications. In this paper, we propose a novel embedded subtree mining algorithm, called Pr...
Many studies of spatiotemporal pattern discovery partition data space into disjoint cells for effective processing. However, the discovery accuracy of the space-partitioning schem...
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
A problem of association rules discovery in a multivariate time series is considered in this paper. A method for finding interpretable association rules between frequent qualitati...