Tarek Hamrouni

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The problem of the relevance and the usefulness of extracted association rules is becoming of primary importance, since an overwhelming number of association rules may be derived, even from reasonably sized databases. To overcome such drawback, the extraction of reduced size generic bases of association rules seems to be promising. Using the concept of(More)
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 clear promise to provide adequate tools and/or techniques to do so, is the discovery of hidden information that can be retrieved from datasets. In this paper, we present a(More)
Providing efficient and easy-to-use graphical tools to users is a promising challenge of data mining (DM). These tools must be able to generate explicit knowledge and to restitute it. Visualization techniques have shown to be an efficient solution to achieve such goal. Even though considered as a key step in the mining process, the visualization step of(More)
Minimal generators (MGs) are the smallest ones (w.r.t. the number of items) among equivalent itemsets sharing a common set of objects, while their associated closed itemset (CI) is the largest one. The pairs composed by MGs and their associated CI divide the itemset lattice into distinct equivalence classes. Such pairs were at the origin of various works(More)
Applying classical association rule extraction framework to dense SAGE data leads to an unmanageably highly sized association rule sets– compounded with their low precision– that often make the perusal of knowledge ineffective, their exploitation time-consuming, and frustrating for the user. To overcome such drawback, we advocate the extraction and(More)
The interest in a further pruning of the set of frequent patterns that can be drawn from real-life datasets is growing up. In fact, it is a quite survival reflex towards providing a manageably-sized and reliable knowledge. This fact is witnessed by the proliferation of what is called concise representation of frequent patterns. In this paper, we propose an(More)
In knowledge mining, current trend is witnessing the emergence of a growing number of works towards defining “concise and lossless” representations. One main motivation behind is: tagging a unified framework for drastically reducing large sized sets of association rules. In this context, generic bases of association rules – whose backbone is the conjunction(More)