Incremental Rule Production: Towards a Uniform Approach for Knowledge Organization. - Mondher Maddouri; Ali Jaoua (IEA/AIE, 1996)

An Incrementa Learning System for Imprecise and Uncertain Knowledge Discovery. - Mondher Maddouri; Samir Elloumi; Ali Jaoua (Inf. Sci., 1998)

A data mining approach based on machine learning techniques to classify biological sequences. - Mondher Maddouri; Mourad Elloumi (Knowl. Based Syst., 2002)

Towards a machine learning approach based on incremental concept formation. - Mondher Maddouri (Intell. Data Anal., 2004)

Encoding of Primary Structures of Biological Macromolecules Within a Data Mining Perspective. - Mondher Maddouri; Mourad Elloumi (J. Comput. Sci. Technol., 2004)

A Formal Concept Analysis Approach to Discover Association Rules from Data. - Mondher Maddouri (CLA, 2005)

New voting strategies designed for the classification of nucleic sequences. - Mourad Elloumi; Mondher Maddouri (Knowl. Inf. Syst., 2005)

Construction d'attributs pour l'extraction de connaissances à partir de séquences biologiques. - Mondher Maddouri; Faouzi Mhamdi (AAFD, 2006)

On Statistical Measures for Selecting Pertinent Formal Concepts to Discover Production Rules from Data. - Mondher Maddouri; Fatma Kaâbi (ICDM Workshops, 2006)

Biological Sequences Encoding for Supervised Classification. - Rabie Saidi; Mondher Maddouri; Engelbert Mephu Nguifo (BIRD, 2007)

Improving Boosting by Exploiting Former Assumptions. - Emna Bahri; Nicolas Nicoloyannis; Mondher Maddouri (MCD, 2007)

Classification supervisée de séquences biologiques basée sur les motifs et les matrices de substitution. - Rabie Saidi; Mondher Maddouri; Engelbert Mephu Nguifo (EGC, 2007)

On Semantic Properties of Interestingness Measures for Extracting Rules from Data. - Mondher Maddouri; Jamil Gammoudi (ICANNGA (1), 2007)

Une nouvelle approche du Boosting face aux données réelles. - Emna Bahri; Mondher Maddouri (EGC, 2008)

Générer des règles de classification par dopage de concepts formels. - Nida Meddouri; Mondher Maddouri (EGC, 2009)

Boosting Formal Concepts to Discover Classification Rules. - Nida Meddouri; Mondher Maddouri (IEA/AIE, 2009)

Comparing graph-based representations of protein for mining purposes. - Rabie Saidi; Mondher Maddouri; Engelbert Mephu Nguifo (KDD Workshop on Statistical and Relational Learning in Bioinformatics, 2009)

A Hybrid Approach of Boosting Against Noisy Data. - Emna Bahri; Stéphane Lallich; Nicolas Nicoloyannis; Mondher Maddouri (Mining Complex Data, 2009)

Développement de méthodes de classification basées sur l'analyse de concepts formels sous la plateforme WEKA. - Besma Khalfi; Rahma Cherif; Nida Meddouri; Mondher Maddouri (EGC, 2010)

Apprentissage supervisé adaptatif de Concepts Formels à partir des données nominales. - Nida Meddouri; Mondher Maddouri (EGC, 2010)

Etude de stabilité de méthodes d'extraction de motifs à partir des séquences protéiques. - Rabie Saidi; Sabeur Aridhi; Mondher Maddouri; Engelbert Mephu Nguifo (EGC, 2010)

Adaptive Learning of Nominal Concepts for Supervised Classification. - Nida Meddouri; Mondher Maddouri (KES (1), 2010)

Protein sequences classification by means of feature extraction with substitution matrices. - Rabie Saidi; Mondher Maddouri; Engelbert Mephu Nguifo (BMC Bioinform., 2010)

Vers un critère d'arrêt de Boosting basé sur la diversité des classifieurs. - Nida Meddouri; Hela Khoufi; Mondher Maddouri (INFORSID, 2011)

Feature extraction in protein sequences classification: a new stability measure. - Rabie Saidi; Sabeur Aridhi; Engelbert Mephu Nguifo; Mondher Maddouri (BCB, 2012)

Diversity Analysis on Boosting Nominal Concepts. - Nida Meddouri; Hela Khoufi; Mondher Maddouri (PAKDD (1), 2012)

Computational phenotype prediction of ionizing-radiation-resistant bacteria with a multiple-instance learning model. - Sabeur Aridhi; Mondher Maddouri; Haïtham Sghaier; Engelbert Mephu Nguifo (BIOKDD, 2013)

Parallel Learning and Classification for Rules based on Formal Concepts. - Nida Meddouri; Hela Khoufi; Mondher Maddouri (KES, 2014)

Un partitionnement basé sur la densité de graphe pour approcher la fouille distribuée de sous-graphes fréquents. - Sabeur Aridhi; Laurent d'Orazio; Mondher Maddouri; Engelbert Mephu Nguifo (Tech. Sci. Informatiques, 2014)

Cost Models for Distributed Pattern Mining in the Cloud. - Sabeur Aridhi; Laurent d'Orazio; Mondher Maddouri; Engelbert Mephu Nguifo (TrustCom/BigDataSE/ISPA (2), 2015)

Density-based data partitioning strategy to approximate large-scale subgraph mining. - Sabeur Aridhi; Laurent d'Orazio; Mondher Maddouri; Engelbert Mephu Nguifo (Inf. Syst., 2015)

New Taxonomy of Classification Methods Based on Formal Concepts Analysis. - Marwa Trabelsi; Nida Meddouri; Mondher Maddouri (FCA4AI@ECAI, 2016)

A multiple instance learning approach for sequence data with across bag dependencies. - Manel Zoghlami; Sabeur Aridhi; Haïtham Sghaier; Mondher Maddouri; Engelbert Mephu Nguifo (CoRR, 2016)

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model. - Sabeur Aridhi; Haïtham Sghaier; Manel Zoghlami; Mondher Maddouri; Engelbert Mephu Nguifo (J. Comput. Biol., 2016)

A New Feature Selection Method for Nominal Classifier based on Formal Concept Analysis. - Marwa Trabelsi; Nida Meddouri; Mondher Maddouri (KES, 2017)

ABClass : Une approche d'apprentissage multi-instances pour les séquences(ABClass: A multiple instance learning approach for sequence data). - Manel Zoghlami; Sabeur Aridhi; Mondher Maddouri; Engelbert Mephu Nguifo (CNIA+RJCIA, 2018)

A Comparative Study on Streaming Frameworks for Big Data. - Wissem Inoubli; Sabeur Aridhi; Haithem Mezni; Mondher Maddouri; Engelbert Mephu Nguifo (LADaS@VLDB, 2018)

An experimental survey on big data frameworks. - Wissem Inoubli; Sabeur Aridhi; Haithem Mezni; Mondher Maddouri; Engelbert Mephu Nguifo (Future Gener. Comput. Syst., 2018)

Cloud Implementation of Classier Nominal Concepts using DistributedWekaSpark. - Rawia Fray; Nida Meddouri; Mondher Maddouri (ICFCA (Supplements), 2019)

A Structure Based Multiple Instance Learning Approach for Bacterial Ionizing Radiation Resistance Prediction. - Manel Zoghlami; Sabeur Aridhi; Mondher Maddouri; Engelbert Mephu Nguifo (KES, 2019)

Efficiently Mining Recurrent Substructures from Protein Three-Dimensional Structure Graphs. - Rabie Saidi; Wajdi Dhifli; Mondher Maddouri; Engelbert Mephu Nguifo (J. Comput. Biol., 2019)

Un algorithme distribué pour le clustering de grands graphes. - Wissem Inoubli; Sabeur Aridhi; Haithem Mezni; Mondher Maddouri; Engelbert Mephu Nguifo (EGC, 2020)

Catégorisation des méthodes de classification fondées sur l'Analyse de Concepts Formels. - Hayfa Azibi; Nida Meddouri; Mondher Maddouri (IC, 2020)

Survey on Formal Concept Analysis Based Supervised Classification Techniques. - Hayfa Azibi; Nida Meddouri; Mondher Maddouri (MLIS, 2020)

Efficient Closure Operators for FCA-Based Classification. - Nida Meddouri; Mondher Maddouri (Int. J. Artif. Intell. Mach. Learn., 2020)

Multiple instance learning for sequence data with across bag dependencies. - Manel Zoghlami; Sabeur Aridhi; Mondher Maddouri; Engelbert Mephu Nguifo (Int. J. Mach. Learn. Cybern., 2020)

DFC: A Performant Dagging Approach of Classification Based on Formal Concept. - Nida Meddouri; Hela Khoufi; Mondher Maddouri (Int. J. Artif. Intell. Mach. Learn., 2021)

A distributed and incremental algorithm for large-scale graph clustering. - Wissem Inoubli; Sabeur Aridhi; Haithem Mezni; Mondher Maddouri; Engelbert Mephu Nguifo (Future Gener. Comput. Syst., 2022)