Logics (DLs) are a family of class based knowledge representation formalisms characterised
by the use of various constructors to build complex classes from simpler ones, and by an …

Association rules are used to investigate large databases. The analyst is usually confronted
with large lists of such rules and has to find the most relevant ones for his purpose. Based on …

As a side effect of the digitalization of unprecedented amount of data, traditional retrieval
tools proved to be unable to extract hidden and valuable knowledge. Data Mining, with a …

Introduction The problem studied in this paper is the road insecurity, which is manifested by
the big number of injuries and deaths recorded annually around the world. These victims of …

Many data mining problems require the discovery of frequent patterns in order to be solved.
Frequent itemsets are useful in the discovery of association rules, episode rules, sequential …

The main topic of this thesis is knowledge discovery in databases (KDD). More precisely, we
have investigated two of the most important tasks of KDD today, namely itemset extraction …

One of the major problems in clausal theorem proving is the control of the proof search. In
the presence of equality, this problem is particularly hard, since nearly all state-of-the-art …

Nous proposons dans cet article l'algorithme Pascal qui introduit une nouvelle optimisation
de l'algorithme de référence Apriori. Cette optimisation est fondée sur le comptage des …

The extremely large number of association rules that can be drawn from–even reasonably
sized datasets, bootstrapped the development of more acute techniques or methods to …

Mining association rules is a leading task, which attracted the attention of researchers, it is
one of the technical potential of data mining that allows discovered correlations and …