Mondher Maddouri

发表

Générer des règles de classification par dopage de concepts formels

Nida Meddouri, Mondher Maddouri, 2009, EGC.

Un partitionnement basé sur la densité de graphe pour approcher la fouille distribuée de sous-graphes fréquents

Sabeur Aridhi, Engelbert Mephu Nguifo, Laurent d'Orazio, 2014, Tech. Sci. Informatiques.

Efficient Closure Operators for FCA-Based Classification

Nida Meddouri, Mondher Maddouri, 2020 .

An Incrementa Learning System for Imprecise and Uncertain Knowledge Discovery

Samir Elloumi, Mondher Maddouri, Ali Jaoua, 1998, Inf. Sci..

Classification supervisée de séquences biologiques basée sur les motifs et les matrices de substitution

Engelbert Mephu Nguifo, Mondher Maddouri, Rabie Saidi, 2007, EGC.

Comparative evaluation of the discovered knowledge

Mondher Maddouri, Ali Jaoua, 1997 .

A data mining approach based on machine learning techniques to classify biological sequences

Mourad Elloumi, Mondher Maddouri, M. Elloumi, 2002, Knowl. Based Syst..

A distributed and incremental algorithm for large-scale graph clustering

Sabeur Aridhi, Engelbert Mephu Nguifo, Haithem Mezni, 2020, Future Gener. Comput. Syst..

Towards a machine learning approach based on incremental concept formation

Mondher Maddouri, Mondher Maddouri, 2004, Intell. Data Anal..

Encoding of primary structures of biological macromolecules within a data mining perspective

Mourad Elloumi, Mondher Maddouri, 2008, Journal of Computer Science and Technology.

Biological Sequences Encoding for Supervised Classification

Engelbert Mephu Nguifo, Mondher Maddouri, Rabie Saidi, 2007, BIRD.

Density-based data partitioning strategy to approximate large-scale subgraph mining

Sabeur Aridhi, Laurent d'Orazio, Engelbert Mephu Nguifo, 2012, Inf. Syst..

Feature extraction in protein sequences classification: a new stability measure

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2012, BCB.

Développement de méthodes de classification basées sur l'analyse de concepts formels sous la plateforme WEKA

Nida Meddouri, Mondher Maddouri, Besma Khalfi, 2010, EGC.

Un partitionnement basé sur la densité de graphe pour approcher la fouille distribuée de sous-graphes fréquents

Sabeur Aridhi, Mondher Maddouri, Engelbert Mephu-Ngifo, 2014 .

Etude de stabilité de méthodes d'extraction de motifs à partir des séquences protéiques

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2010, EGC.

ABClass : Une approche d'apprentissage multi-instances pour les séquences(ABClass: A multiple instance learning approach for sequence data)

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2018, CNIA+RJCIA.

A Novel Scalable Clustering Method for Distributed Networks

Sabeur Aridhi, Engelbert Mephu Nguifo, Haithem Mezni, 2020 .

A large-scale and fault-tolerant approach of subgraph mining using density-based partitioning pdf

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2012, ArXiv.

Efficiently Mining Recurrent Substructures from Protein Three-Dimensional Structure Graphs

Wajdi Dhifli, Engelbert Mephu Nguifo, Mondher Maddouri, 2019, J. Comput. Biol..

Un algorithme distribué pour le clustering de grands graphes

Sabeur Aridhi, Engelbert Mephu Nguifo, Haithem Mezni, 2020, EGC.

A multiple instance learning approach for sequence data with across bag dependencies

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2016 .

Cost Models for Distributed Pattern Mining in the Cloud

Sabeur Aridhi, Laurent d'Orazio, Engelbert Mephu Nguifo, 2015, TrustCom 2015.

Apprentissage supervisé adaptatif de Concepts Formels à partir des données nominales

Nida Meddouri, Mondher Maddouri, 2010, EGC.

A Formal Concept Analysis Approach to Discover Association Rules from Data

Mondher Maddouri, 2005, CLA.

Adaptive Learning of Nominal Concepts for Supervised Classification

Nida Meddouri, Mondher Maddouri, Mondher Maddouri, 2010, KES.

Boosting Formal Concepts to Discover Classification Rules

Nida Meddouri, Mondher Maddouri, Mondher Maddouri, 2009, IEA/AIE.

Une nouvelle approche du Boosting face aux données réelles

Mondher Maddouri, Emna Bahri, 2008, EGC.

New voting strategies designed for the classification of nucleic sequences

Mourad Elloumi, Mondher Maddouri, M. Elloumi, 2005, Knowledge and Information Systems.

New Taxonomy of Classification Methods Based on Formal Concepts Analysis

Nida Meddouri, Mondher Maddouri, Marwa Trabelsi, 2016, FCA4AI@ECAI.

A Structure Based Multiple Instance Learning Approach for Bacterial Ionizing Radiation Resistance Prediction

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2019, KES.

Parallel Learning and Classification for Rules based on Formal Concepts

Nida Meddouri, Mondher Maddouri, Hela Khoufi, 2014, KES.

A Hybrid Approach of Boosting Against Noisy Data

Stéphane Lallich, Mondher Maddouri, Emna Bahri, 2009, Mining Complex Data.

Computational phenotype prediction of ionizing-radiation-resistant bacteria with a multiple-instance learning model

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2013, BioKDD '13.

Diversity Analysis on Boosting Nominal Concepts

Nida Meddouri, Mondher Maddouri, Hela Khoufi, 2012, PAKDD.

Cost Models for Distributed Pattern Mining in the Cloud

Sabeur Aridhi, Engelbert Mephu Nguifo, Laurent d'Orazio, 2015, 2015 IEEE Trustcom/BigDataSE/ISPA.

Comparing graph-based representations of protein for mining purposes

Engelbert Mephu Nguifo, Mondher Maddouri, Rabie Saidi, 2009, StReBio '09.

An experimental survey on big data frameworks (Highlight paper)

Sabeur Aridhi, Engelbert Mephu Nguifo, Haithem Mezni, 2018 .

An experimental survey on big data frameworks

Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, 2016, Future Gener. Comput. Syst..

Incremental Rule Production: Towards a Uniform Approach for Knowledge Organization

Mondher Maddouri, Ali Jaoua, 1996, IEA/AIE.

Protein sequences classification by means of feature extraction with substitution matrices

Engelbert Mephu Nguifo, Mondher Maddouri, Rabie Saidi, 2010, BMC Bioinformatics.

Cloud Implementation of Classier Nominal Concepts using DistributedWekaSpark

Nida Meddouri, Mondher Maddouri, Rawia Fray, 2019, ICFCA.

Catégorisation des méthodes de classification fondées sur l'Analyse de Concepts Formels

Nida Meddouri, Mondher Maddouri, Hayfa Azibi, 2020, IC.

On Semantic Properties of Interestingness Measures for Extracting Rules from Data

Mondher Maddouri, Jamil Gammoudi, Mondher Maddouri, 2007, ICANNGA.

Survey on Formal Concept Analysis based supervised classification techniques

Nida Meddouri, Mondher Maddouri, Hayfa Azibi, 2020, ICML 2020.

A Comparative Study on Streaming Frameworks for Big Data

Sabeur Aridhi, Engelbert Mephu Nguifo, Haithem Mezni, 2018, LADaS@VLDB.

Vers un critère d'arrêt de Boosting basé sur la diversité des classifieurs

Nida Meddouri, Mondher Maddouri, Hela Khoufi, 2011, INFORSID.

On Statistical Measures for Selecting Pertinent Formal Concepts to Discover Production Rules from Data

Mondher Maddouri, Fatma Kaâbi, 2006, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06).

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2016, J. Comput. Biol..

Improving Boosting by Exploiting Former Assumptions

Mondher Maddouri, Emna Bahri, Nicolas Nicoloyannis, 2007, MCD.

Construction d'attributs pour l'extraction de connaissances à partir de séquences biologiques

Mondher Maddouri, Faouzi Mhamdi, Mondher Maddouri, 2006, AAFD.

Multiple instance learning for sequence data with across bag dependencies

Sabeur Aridhi, Engelbert Mephu Nguifo, Mondher Maddouri, 2020, Int. J. Mach. Learn. Cybern..

A New Feature Selection Method for Nominal Classifier based on Formal Concept Analysis

Nida Meddouri, Mondher Maddouri, Marwa Trabelsi, 2017, KES.

DFC: A Performant Dagging Approach of Classification Based on Formal Concept

Nida Meddouri, Mondher Maddouri, Hela Khoufi, 2021, Int. J. Artif. Intell. Mach. Learn..