A K-means-based Algorithm for Projective Clustering. - Mohamed Bouguessa; Shengrui Wang; Qingshan Jiang (ICPR (1), 2006)

An objective approach to cluster validation. - Mohamed Bouguessa; Shengrui Wang; Haojun Sun (Pattern Recognit. Lett., 2006)

PCGEN: A Practical Approach to Projected Clustering and its Application to Gene Expression Data. - Mohamed Bouguessa; Shengrui Wang (CIDM, 2007)

Identifying authoritative actors in question-answering forums: the case of Yahoo! answers. - Mohamed Bouguessa; Benoît Dumoulin; Shengrui Wang (KDD, 2008)

Mining Projected Clusters in High-Dimensional Spaces. - Mohamed Bouguessa; Shengrui Wang (IEEE Trans. Knowl. Data Eng., 2009)

Discovering Knowledge-Sharing Communities in Question-Answering Forums. - Mohamed Bouguessa; Shengrui Wang; Benoît Dumoulin (ACM Trans. Knowl. Discov. Data, 2010)

An Unsupervised Approach for Identifying Spammers in Social Networks. - Mohamed Bouguessa (ICTAI, 2011)

A Practical Approach for Clustering Transaction Data. - Mohamed Bouguessa (MLDM, 2011)

Modeling Outlier Score Distributions. - Mohamed Bouguessa (ADMA, 2012)

Unsupervised Anomaly Detection in Transactional Data. - Mohamed Bouguessa (ICMLA (1), 2012)

A Probabilistic Combination Approach to Improve Outlier Detection. - Mohamed Bouguessa (ICTAI, 2012)

Document Modeling Using Syntactic and Semantic Information. - Emilie Au; Mohamed Bouguessa; Shengrui Wang (AINA Workshops, 2013)

A Novel Approach for Detecting Community Structure in Networks. - Mohamed Bouguessa; Rokia Missaoui; Mohamed Talbi (ICTAI, 2014)

A Mixture Model-Based Combination Approach for Outlier Detection. - Mohamed Bouguessa (Int. J. Artif. Intell. Tools, 2014)

A model-based approach for identifying spammers in social networks. - Farnoosh Fathaliani; Mohamed Bouguessa (DSAA, 2015)

Tracking the evolution of community structures in time-evolving social networks. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (DSAA, 2015)

Clustering categorical data in projected spaces. - Mohamed Bouguessa (Data Min. Knowl. Discov., 2015)

A practical outlier detection approach for mixed-attribute data. - Mohamed Bouguessa (Expert Syst. Appl., 2015)

Identifying Authorities in Online Communities. - Mohamed Bouguessa; Lotfi Ben Romdhane 001 (ACM Trans. Intell. Syst. Technol., 2015)

Using Support Vector Machines for Intelligent Service Agents Decision Making. - Babak Khosravifar; Mohamed Bouguessa (MLDM, 2016)

Tracking Communities over Time in Dynamic Social Network. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (MLDM, 2016)

MCDA: A Parameterless Algorithm for Detecting Communities in Multidimensional Networks. - Oualid Boutemine; Mohamed Bouguessa (ASONAM, 2017)

Identifying Anomalous Nodes in Multidimensional Networks. - Amani Chouchane; Mohamed Bouguessa (DSAA, 2017)

A Comparative Study of Different Approaches for Tracking Communities in Evolving Social Networks. - Ziwei He; Etienne Gael Tajeuna; Shengrui Wang; Mohamed Bouguessa (DSAA, 2017)

Detecting Large Concept Extensions for Conceptual Analysis. - Louis Chartrand; Jackie Chi Kit Cheung; Mohamed Bouguessa (MLDM, 2017)

Survival analysis for modeling critical events that communities may undergo in dynamic social networks. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (SAC, 2017)

Mining Community Structures in Multidimensional Networks. - Oualid Boutemine; Mohamed Bouguessa (ACM Trans. Knowl. Discov. Data, 2017)

A Statistical Framework for Handling Network Anomalies. - Mohamed Bouguessa; Amani Chouchane (ASONAM, 2018)

A Network-Based Approach to Enhance Electricity Load Forecasting. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (ICDM Workshops, 2018)

Sniffing Android code smells: an association rules mining-based approach. - Jehan Rubin; Adel Nassim Henniche; Naouel Moha; Mohamed Bouguessa; Nabila Bousbia (MOBILESoft@ICSE, 2019)

Modeling and Predicting Community Structure Changes in Time-Evolving Social Networks. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (IEEE Trans. Knowl. Data Eng., 2019)

Context Matters: Self-Attention for Sign Language Recognition. - Fares Ben Slimane; Mohamed Bouguessa (ICPR, 2020)

Exploring the representational power of graph autoencoder. - Maroun Haddad; Mohamed Bouguessa (Neurocomputing, 2021)

TopoDetect: Framework for topological features detection in graph embeddings. - Maroun Haddad; Mohamed Bouguessa (Softw. Impacts, 2021)

BiNeTClus: Bipartite Network Community Detection Based on Transactional Clustering. - Mohamed Bouguessa; Khaled Nouri (ACM Trans. Intell. Syst. Technol., 2021)

Mining Customers' Changeable Electricity Consumption for Effective Load Forecasting. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (ACM Trans. Intell. Syst. Technol., 2021)

A Time-Dependent-Based Approach to Enhance Self-Harm Prediction. - Etienne Gael Tajeuna; Mohamed Bouguessa (ASONAM, 2022)

A Longitudinal Study of Customer Electricity Load Profiles. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (COMPSAC, 2022)

Graph Attention Network for Camera Relocalization on Dynamic Scenes. - Mohamed Amine Ouali; Mohamed Bouguessa; Riadh Ksantini (DSAA, 2022)

Escaping Feature Twist: A Variational Graph Auto-Encoder for Node Clustering. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (IJCAI, 2022)

Dynamic Cox-Regression for Motif Prediction in Co-Evolving Time Series Data. - Etienne Gael Tajeuna; Mohamed Bouguessa (IJCNN, 2022)

Adversarial Deep Embedded Clustering: On a Better Trade-off Between Feature Randomness and Feature Drift. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (IEEE Trans. Knowl. Data Eng., 2022)

Exploring the Interaction between Local and Global Latent Configurations for Clustering Single-Cell RNA-Seq: A Unified Perspective. - Nairouz Mrabah; Mohamed Mahmoud Amar; Mohamed Bouguessa; Abdoulaye Baniré Diallo (AAAI, 2023)

Tracking User Sentiment Changes on Social Networks. - Ahmed F. M. Fahmy; Etienne Gael Tajeuna; Mohamed Bouguessa (ASONAM, 2023)

Modeling Time-Varying User Attitudes in Social Media. - Etienne Gael Tajeuna; Ahmed F. M. Fahmy; Mohamed Bouguessa (COMPSAC, 2023)

Adversarial Deep Embedded Clustering: On a better trade-off between Feature Randomness and Feature Drift (Extended abstract). - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (ICDE, 2023)

Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering (Extended abstract). - Nairouz Mrabah; Mohamed Bouguessa; Mohamed Fawzi Touati; Riadh Ksantini (ICDE, 2023)

Toward Convex Manifolds: A Geometric Perspective for Deep Graph Clustering of Single-cell RNA-seq Data. - Nairouz Mrabah; Mohamed Mahmoud Amar; Mohamed Bouguessa; Abdoulaye Baniré Diallo (IJCAI, 2023)

Beyond The Evidence Lower Bound: Dual Variational Graph Auto-Encoders For Node Clustering. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (SDM, 2023)

Modeling Regime Shifts in Multiple Time Series. - Etienne Gael Tajeuna; Mohamed Bouguessa; Shengrui Wang (ACM Trans. Knowl. Discov. Data, 2023)

Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering. - Nairouz Mrabah; Mohamed Bouguessa; Mohamed Fawzi Touati; Riadh Ksantini (IEEE Trans. Knowl. Data Eng., 2023)

MLCDG: Multi-Level Contrastive Graph Clustering in Dynamic Graphs. - Mohamed Mahmoud Amar; Mohamed Bouguessa; Abdoulaye Baniré Diallo (ASONAM (3), 2024)

A Geometric Perspective for High-Dimensional Multiplex Graphs. - Kamel Abdous; Nairouz Mrabah; Mohamed Bouguessa (CIKM, 2024)

Towards Robust Time-to-Event Prediction: Integrating the Variational Information Bottleneck with Neural Survival Model. - Armand Bandiang Massoua; Abdoulaye Baniré Diallo; Mohamed Bouguessa (IJCNN, 2024)

DfHM: A Hierarchical Approach for Matching Pairs of Images Using Graph Attention Neural Networks. - Mohamed Amine Ouali; Mohamed Bouguessa; Riadh Ksantini (IJCNN, 2024)

A contrastive variational graph auto-encoder for node clustering. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (Pattern Recognit., 2024)

Hierarchical Aggregations for High-Dimensional Multiplex Graph Embedding. - Kamel Abdous; Nairouz Mrabah; Mohamed Bouguessa (IEEE Trans. Knowl. Data Eng., 2024)