Knowledge reduction is one of the basic issues in knowledge presentation and data mining.
In this study, an order-preserving map** between the set of all the extensions of the …

Revealing the community structure in social networks witnessed a determined effort. In this
respect, a different category of social network can be handled, such as, dynamic social …

Association rule mining among itemsets is a fundamental task and is of great importance in
many data mining applications including attacks in network data, stock market, financial …

It is widely recognized that the performances of frequent-pattern mining algorithms are
closely dependent on data being handled, ie, sparse or dense. The same situation applies …

Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up
to now, there have been several types of rules in formal decision contexts. However, these …

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

Concise representations of frequent itemsets sacrifice readability and direct interpretability
by a data analyst of the concise patterns extracted. In this paper, we introduce an extension …

Pattern extraction is one of the major topics in the Knowledge Discovery from Data (KDD)
and Background Knowledge Integration (BKI) research domains. Extracting patterns from …

The output of an association rule miner is often huge in practice. This is why several concise
lossless representations have been proposed, such as the “essential” or “representative” …

The effective use of the concept lattice in large datasets has been always limited by the large
volume of extracted knowledge. The stability measure has been shown to be of valuable …