Big Data Frameworks: A Comparative Study. - Wissem Inoubli; Sabeur Aridhi; Haithem Mezni; Alexander Jung (CoRR, 2016)

A Distributed Framework for Large-Scale Time-Dependent Graph Analysis. - Wissem Inoubli; Lívia Almada Cruz; Ticiana Linhares Coelho da Silva; Gustavo Coutinho; Lucas Peres; Regis Pires Magalhães; José Antônio Fernandes de Macêdo; Sabeur Aridhi; Engelbert Mephu Nguifo (TD-LSG@PKDD/ECML, 2017)

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)

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

Distributed Scalable Association Rule Mining over Covid-19 Data. - Mahtab Shahin; Wissem Inoubli; Syed Attique Shah; Sadok Ben Yahia; Dirk Draheim (FDSE, 2021)

Pregnancy Associated Breast Cancer Gene Expressions : New Insights on Their Regulation Based on Rare Correlated Patterns. - Souad Bouasker; Wissem Inoubli; Sadok Ben Yahia; Gayo Diallo (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Analysis and Mining of Large Dynamic Graphs: case of graph clustering. (Fouille et Analyse de Grands Graphes Dynamiques : Application dans le clustering de graphes). - Wissem Inoubli (2021)

DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification. - Wissem Inoubli; Armelle Brun (HR@RecSys, 2022)

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)

Graph Representation Learning for Recommendation Systems: A Short Review. - Khouloud Ammar; Wissem Inoubli; Sami Zghal; Engelbert Mephu Nguifo (ICIKS, 2023)

DGCN: Learning Graph Representations Via Dense Connections. - Khairi Abidi; Wissem Inoubli; Engelbert Mephu Nguifo (KES, 2023)

Trans-Trip: Translation-based embedding with Triplets for Heterogeneous Graphs. - Khouloud Ammar; Wissem Inoubli; Sami Zghal; Amel Borji; Engelbert Mephu Nguifo (KES, 2023)

Learning From Few Cyber-Attacks: Addressing the Class Imbalance Problem in Machine Learning-Based Intrusion Detection in Software-Defined Networking. - Seyed Mohammad Hadi Mirsadeghi; Hayretdin Bahsi; Risto Vaarandi; Wissem Inoubli (IEEE Access, 2023)

Scaling Knowledge Graph Embedding with Parallel TransE and Graph Partitioning. - Khouloud Ammar; Wissem Inoubli; Sami Zghal; Engelbert Mephu Nguifo (AICCSA, 2024)

Un algorithme d'apprentissage profond et semi-supervisé basé sur la représentation de graphes pour la classification des CV. - Wissem Inoubli; Armelle Brun (EGC, 2024)

Large-scale knowledge graph representation learning. - Marwa Badrouni; Chaker Katar; Wissem Inoubli (Knowl. Inf. Syst., 2024)

Knowledge graph representation learning: A comprehensive and experimental overview. - Dorsaf Sellami; Wissem Inoubli; Imed Riadh Farah; Sabeur Aridhi (Comput. Sci. Rev., 2025)

Navigating complexity: a comprehensive review of heterogeneous information networks and embedding techniques. - Khouloud Ammar; Wissem Inoubli; Sami Zghal; Engelbert Mephu Nguifo (Knowl. Inf. Syst., 2025)