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Un nouvel algorithme d'extraction des motifs graduels appelé Sgrite : Extraction des motifs graduels

Abstract : The extraction of frequent gradual patterns is an important problem in computer science and largely studied by the scientist's community of research in data mining. A frequent gradual pattern translates a recurrent covariation between the attributes of a database. Many applications issues from many domains, such as economy, health, education, market, bio-informatics, astronomy, or web mining, are based on the extraction of frequent gradual patterns. Algorithms to extract frequent gradual patterns in the large databases are greedy in CPU time and memory space. This raises the problem of improving the performances of these algorithms. This paper presents a technique for improving the performance of frequent gradual pattern extraction algorithms. The exploitation of this technique leads to a new, more efficient algorithm called Sgrite. The experiments carried out confirm the interest of the proposed technique.
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Contributor : Laurent Cabrel Tabueu Fotso Connect in order to contact the contributor
Submitted on : Monday, August 31, 2020 - 12:19:00 AM
Last modification on : Friday, September 4, 2020 - 4:28:55 PM
Long-term archiving on: : Tuesday, December 1, 2020 - 12:05:21 PM


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  • HAL Id : hal-02925778, version 1



Tayou Djamégni Clémentin, Tabueu Fotso Laurent Cabrel, Kenmogne Belise. Un nouvel algorithme d'extraction des motifs graduels appelé Sgrite : Extraction des motifs graduels. CARI 2020 - Colloque Africain sur la Recherche en Informatique et en Mathémathiques Appliquées, Oct 2020, Thiès, Sénégal. ⟨hal-02925778⟩



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