One of the main problems raising up in the frequent closed itemsets mining problem is the duplicate detection. In this paper we propose a general technique for promptly detecting ...
We introduce a novel framework (BLOSOM) for mining (frequent) boolean expressions over binary-valued datasets. We organize the space of boolean expressions into four categories: p...
Lizhuang Zhao, Mohammed J. Zaki, Naren Ramakrishna...
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
A number of vertical mining algorithms have been proposed recently for association mining, which have shown to be very effective and usually outperform horizontal approaches. The ...
Privacy considerations often constrain data mining projects. This paper addresses the problem of association rule mining where transactions are distributed across sources. Each si...