Proceedings and editorials
[P1] W. Inoubli, S. Aridhi J.A. Fernandes de Macêdo, E. Mephu Nguifo and K. Zeitouni. Proceedings of the Workshop on Advances in managing and mining large evolving graphs (LEG) co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2020), Ghent Belgium, 14-18 September 2020.
Papers in journals with reviewing committee
[J4] W. Inoubli , S. Aridhi, H. Mezni, M. Maddouri, E. M. Nguifo. A Distributed and Incremental Algorithm for Large-Scale Graph Clustering. Future Generation Computer Systems, Elsevier, 134, pp. 334-347, 2022. [IF = 7.187]
[J3] A. Mouakhera, W. Inoubli, C. Ounoughib, A. Koa. PExpect: EXplainable Prediction model for Energy ConsumpTion. Mathematics, 2020 [IF = 2.258]
[J2] S. Bouasker, W. Inoubli, S. Ben Yahia and G. Diallo. Pregnancy Associated Breast Cancer gene expressions : new insights on their regulation based on Rare Correlated Patterns.
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020 [IF = 3.015]
[J1] W. Inoubli , S. Aridhi, H. Mezni, M. Maddouri, E. M. Nguifo. An Experimental Survey on Big Data Frameworks. Future Generation Computer Systems, Elsevier, 86, pp. 546-564, 2018. [Publisher’s version] [Supplementary material] [IF = 5.768]
International conferences/workshops with program committee
[IC7] K. Ammar, W. Inoubli , S. Zghal and E.M Nguifo Graph Representation Learning for Recommendation Systems: A short review. 6th International Conference on Information and Knowledge Systems (ICIKS), 22nd to the 23rd of June, 2023, Portsmouth, UK.
[IC6] H .Mirsadeghi,H. Bahsi, W. Inoubli Deep Learning-based Detection of Cyberattacks in Sofware-Defined Networks. 13th EAI International Conference on Digital Forensics & Cyber Crime, November 16-18, 2022, Boston, United States.
[IC5] W. Inoubli , A. Brun DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification. RecSys in HR’22: The 2nd Workshop on Recommender Systems for Human Resources, in conjunction with the 16th ACM Conference on Recommender Systems, September 18–23, 2022, Seattle, USA .
[IC4] M. Shahin, W. Inoubli, S. Attique Shah, S. Ben Yahia and D. Draheim. Distributed Scalable Association Rule Mining Over Covid-19 Data. International Conference on Future Data and Security Engineering (FDSE). Virtual Mode, November 24-26, 2021.
[IC3] W. Inoubli , S. Aridhi, H. Mezni, M. Maddouri and E. Mephu Nguifo. A Comparative Study on Streaming Frameworks for Big Data . Proceedings of the Latin America Data Science Workshop co-located with 44th International Conference on Very Large Data Bases (VLDB 2018), Rio de Janeiro, Brazil, Aug 27, 2018 .
[IC2] W. Inoubli,S. Aridhi, H. Mezni, M. Maddouri and E. Mephu Nguifo. An Experimental Survey on Big Data Frameworks. Extremely Large Databases Conference (XLDB) 2017, Clermont Ferrand, France. (Lightning talk, poster)
[IC1] W. Inoubli, L. Almada, T.L. Coelho da Silva, G. Coutinho, L. Peres, R.P. Magalhaes, J.F. de Macedo, S. Aridhi, E. Mephu Nguifo. A Distributed Framework for Large-Scale Time-Dependent Graph Analysis. Joint Workshop on Large-Scale Evolving Networks and Graphs in conjunction with ECML-PKDD 2017, Skopje, Macedonia.
National conferences with program committee
[NC2] W. Inoubli, S. Aridhi, H. Mezni, M. Maddouri, E. M. Nguifo. Un algorithme distribué pour le clustering de grands graphes. Extraction et Gestion des Connaissances (EGC 2020), Bruxelles, Belgique.
[NC1] W. Inoubli, S. Aridhi, H. Mezni, M. Maddouri, E. M. Nguifo. An Experimental Survey on Big Data Frameworks. 34-èmes journées de la conférence « Gestion de Données – Principes, Technologies et Applications » (BDA 2018), Bucarest, Romania. [Supplementary material]