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2020 – today
- 2024
[j5]Marwa Badrouni, Chaker Katar, Wissem Inoubli:
Large-scale knowledge graph representation learning. Knowl. Inf. Syst. 66(9): 5479-5499 (2024)- [c9]Wissem Inoubli, Armelle Brun:
Un algorithme d'apprentissage profond et semi-supervisé basé sur la représentation de graphes pour la classification des CV. EGC 2024: 401-408 - 2023
- [j4]Seyed Mohammad Hadi Mirsadeghi
, Hayretdin Bahsi, Risto Vaarandi, Wissem Inoubli:
Learning From Few Cyber-Attacks: Addressing the Class Imbalance Problem in Machine Learning-Based Intrusion Detection in Software-Defined Networking. IEEE Access 11: 140428-140442 (2023) - [c8]Khouloud Ammar, Wissem Inoubli, Sami Zghal, Engelbert Mephu Nguifo:
Graph Representation Learning for Recommendation Systems: A Short Review. ICIKS 2023: 33-48 - [c7]Khairi Abidi, Wissem Inoubli, Engelbert Mephu Nguifo:
DGCN: Learning Graph Representations Via Dense Connections. KES 2023: 951-960 - [c6]Khouloud Ammar, Wissem Inoubli, Sami Zghal, Amel Borji, Engelbert Mephu Nguifo:
Trans-Trip: Translation-based embedding with Triplets for Heterogeneous Graphs. KES 2023: 1104-1113 - 2022
- [j3]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, Engelbert Mephu Nguifo:
A distributed and incremental algorithm for large-scale graph clustering. Future Gener. Comput. Syst. 134: 334-347 (2022) - [c5]Wissem Inoubli, Armelle Brun:
DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification. HR@RecSys 2022 - 2021
- [b1]Wissem Inoubli:
Analysis and Mining of Large Dynamic Graphs: case of graph clustering. (Fouille et Analyse de Grands Graphes Dynamiques : Application dans le clustering de graphes). Tunis El Manar University, Tunisia, 2021 - [j2]Souad Bouasker, Wissem Inoubli, Sadok Ben Yahia, Gayo Diallo:
Pregnancy Associated Breast Cancer Gene Expressions : New Insights on Their Regulation Based on Rare Correlated Patterns. IEEE ACM Trans. Comput. Biol. Bioinform. 18(3): 1035-1048 (2021) - [c4]Mahtab Shahin, Wissem Inoubli, Syed Attique Shah, Sadok Ben Yahia, Dirk Draheim:
Distributed Scalable Association Rule Mining over Covid-19 Data. FDSE 2021: 39-52 - 2020
- [c3]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, Engelbert Mephu Nguifo:
Un algorithme distribué pour le clustering de grands graphes. EGC 2020: 349-356
2010 – 2019
- 2018
- [j1]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, Engelbert Mephu Nguifo:
An experimental survey on big data frameworks. Future Gener. Comput. Syst. 86: 546-564 (2018) - [c2]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, Engelbert Mephu Nguifo:
A Comparative Study on Streaming Frameworks for Big Data. LADaS@VLDB 2018: 17-24 - 2017
- [c1]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:
A Distributed Framework for Large-Scale Time-Dependent Graph Analysis. TD-LSG@PKDD/ECML 2017: 48-53 - 2016
- [i1]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Alexander Jung:
Big Data Frameworks: A Comparative Study. CoRR abs/1610.09962 (2016)
Coauthor Index
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