Concise (or condensed) representations of frequent patterns follow the minimum description
length (MDL) principle, by providing the shortest description of the whole set of frequent …

Several efforts were devoted to mining association rules having conjunction of items in
premise and conclusion parts. Such rules convey information about the co-occurrence …

A new approach to vertical fragmentation in relational databases is proposed using
association rules, a data-mining technique. Vertical fragmentation can enhance the …

The last years witnessed an explosive progress in networking, storage, and processing
technologies resulting in an unprecedented amount of digitalization of data. Hence, there …

In association rule mining, support is a measure of association between two sets of items,
which indicates the relative occurrence of both sets within the overall set of transactions. In …

Association rule mining discovers relationships among items in a transactional database.
Most approaches assume that all items within a dataset have a uniform distribution with …

A convenient application domain in biology is gene expression data, which include a large
number of attributes (genes), and the associations among different genes are often …

The best known and most widely utilized pattern finding algorithm in data mining
applications is association rule mining (ARM). Extraction of frequent patterns is an …

In this paper the authors present a novel method for finding optimal split points for
discretization of continuous attributes. Such a method can be used in many data mining …

A thorough scrutiny of the literature dedicated to association rule mining highlights that a
determined effort focused so far on mining the co-occurrence relations between items, ie …