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Sabeur Aridhi
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2020 – today
- 2023
- [b2]Sabeur Aridhi:
Découverte de connaissances à partir de grands graphes biologiques. (Knowledge discovery from large biological graphs / Knowledge discovery from large biological graphs: Knowledge discovery from large biological graphs). University of Lorraine, Nancy, France, 2023 - [j22]Nour El Islem Karabadji
, Abdelaziz Amara Korba, Ali Assi
, Hassina Seridi, Sabeur Aridhi, Wajdi Dhifli
:
Accuracy and diversity-aware multi-objective approach for random forest construction. Expert Syst. Appl. 225: 120138 (2023) - 2022
- [j21]Bishnu Sarker
, Navya Khare, Marie-Dominique Devignes, Sabeur Aridhi
:
Improving automatic GO annotation with semantic similarity. BMC Bioinform. 23-S(2): 433 (2022) - [j20]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) - [j19]Marcelo B. A. Veras, Bishnu Sarker
, Sabeur Aridhi, João P. P. Gomes
, José A. F. de Macêdo
, Engelbert Mephu Nguifo
, Marie-Dominique Devignes, Malika Smaïl-Tabbone:
On the design of a similarity function for sparse binary data with application on protein function annotation. Knowl. Based Syst. 238: 107863 (2022) - [j18]Md. Kamrul Islam, Sabeur Aridhi, Malika Smaïl-Tabbone:
Negative sampling and rule mining for explainable link prediction in knowledge graphs. Knowl. Based Syst. 250: 109083 (2022) - [c18]Akrem Sellami
, Bishnu Sarker
, Salvatore Tabbone
, Marie-Dominique Devignes
, Sabeur Aridhi
:
A Semi-supervised Graph Deep Neural Network for Automatic Protein Function Annotation. IWBBIO (2) 2022: 153-166 - 2021
- [j17]Haithem Mezni
, Mokhtar Sellami
, Sabeur Aridhi, Faouzi Ben Charrada:
Towards big services: a synergy between service computing and parallel programming. Computing 103(11): 2479-2519 (2021) - [c17]Md. Kamrul Islam
, Sabeur Aridhi, Malika Smaïl-Tabbone:
Simple Negative Sampling for Link Prediction in Knowledge Graphs. COMPLEX NETWORKS 2021: 549-562 - 2020
- [j16]Bishnu Sarker
, David W. Ritchie, Sabeur Aridhi
:
GrAPFI: predicting enzymatic function of proteins from domain similarity graphs. BMC Bioinform. 21(1): 168 (2020) - [j15]Sabeur Aridhi, José A. F. de Macêdo, Engelbert Mephu Nguifo, Karine Zeitouni
:
Special issue on "Advances on Large Evolving Graphs". Future Gener. Comput. Syst. 110: 310 (2020) - [j14]Manel Zoghlami
, Sabeur Aridhi, Mondher Maddouri, Engelbert Mephu Nguifo:
Multiple instance learning for sequence data with across bag dependencies. Int. J. Mach. Learn. Cybern. 11(3): 629-642 (2020) - [c16]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, Engelbert Mephu Nguifo:
Un algorithme distribué pour le clustering de grands graphes. EGC 2020: 349-356 - [c15]Bishnu Sarker
, Navya Khare, Marie-Dominique Devignes, Sabeur Aridhi:
Graph Based Automatic Protein Function Annotation Improved by Semantic Similarity. IWBBIO 2020: 261-272 - [i8]Md. Kamrul Islam, Sabeur Aridhi, Malika Smaïl-Tabbone:
A comparative study of similarity-based and GNN-based link prediction approaches. CoRR abs/2008.08879 (2020)
2010 – 2019
- 2019
- [j13]Nour El Islem Karabadji
, Ilyes Khelf, Hassina Seridi, Sabeur Aridhi, Didier Rémond
, Wajdi Dhifli
:
A data sampling and attribute selection strategy for improving decision tree construction. Expert Syst. Appl. 129: 84-96 (2019) - [j12]Allel Hadjali, Haithem Mezni
, Sabeur Aridhi, Andrei Tchernykh
:
Special issue on "Uncertainty in Cloud Computing: Concepts, Challenges and Current Solutions". Int. J. Approx. Reason. 111: 53-55 (2019) - [c14]Bishnu Sarker
, David W. Ritchie, Sabeur Aridhi:
Functional Annotation of Proteins using Domain Embedding based Sequence Classification. KDIR 2019: 163-170 - [c13]Manel Zoghlami, Sabeur Aridhi, Mondher Maddouri, Engelbert Mephu Nguifo:
A Structure Based Multiple Instance Learning Approach for Bacterial Ionizing Radiation Resistance Prediction. KES 2019: 342-351 - 2018
- [j11]Nour El Islem Karabadji, Samia Beldjoudi, Hassina Seridi, Sabeur Aridhi, Wajdi Dhifli
:
Improving memory-based user collaborative filtering with evolutionary multi-objective optimization. Expert Syst. Appl. 98: 153-165 (2018) - [j10]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) - [j9]Haithem Mezni
, Sabeur Aridhi, Allel Hadjali:
The uncertain cloud: State of the art and research challenges. Int. J. Approx. Reason. 103: 139-151 (2018) - [c12]Bishnu Sarker
, David W. Ritchie, Sabeur Aridhi:
Exploiting Complex Protein Domain Networks for Protein Function Annotation. COMPLEX NETWORKS (2) 2018: 598-610 - [c11]Manel Zoghlami, Sabeur Aridhi, Mondher Maddouri, Engelbert Mephu Nguifo:
ABClass : Une approche d'apprentissage multi-instances pour les séquences(ABClass: A multiple instance learning approach for sequence data). CNIA+RJCIA 2018: 10-18 - [c10]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
- [j8]Sabeur Aridhi
, Alberto Montresor
, Yannis Velegrakis
:
BLADYG: A Graph Processing Framework for Large Dynamic Graphs. Big Data Res. 9: 9-17 (2017) - [j7]Wajdi Dhifli
, Sabeur Aridhi
, Engelbert Mephu Nguifo
:
MR-SimLab: Scalable subgraph selection with label similarity for big data. Inf. Syst. 69: 155-163 (2017) - [j6]Nour El Islem Karabadji
, Hassina Seridi, Fouad Bousetouane, Wajdi Dhifli
, Sabeur Aridhi
:
An evolutionary scheme for decision tree construction. Knowl. Based Syst. 119: 166-177 (2017) - [c9]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 - [e1]Sabeur Aridhi, José Antônio Fernandes de Macêdo, Engelbert Mephu Nguifo, Karine Zeitouni:
Proceedings of the Workshop on Large-Scale Time Dependent Graphs (TD-LSG 2017) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. CEUR Workshop Proceedings 1929, CEUR-WS.org 2017 [contents] - [i7]Sabeur Aridhi, Alberto Montresor, Yannis Velegrakis:
BLADYG: A Graph Processing Framework for Large Dynamic Graphs. CoRR abs/1701.00546 (2017) - [i6]Sabeur Aridhi, Seyed Ziaeddin Alborzi, Malika Smaïl-Tabbone, Marie-Dominique Devignes, David W. Ritchie:
Neighborhood-Based Label Propagation in Large Protein Graphs. CoRR abs/1708.07074 (2017) - 2016
- [j5]Sabeur Aridhi
, Engelbert Mephu Nguifo
:
Big Graph Mining: Frameworks and Techniques. Big Data Res. 6: 1-10 (2016) - [j4]Sabeur Aridhi
, Haïtham Sghaier
, Manel Zoghlami, Mondher Maddouri, Engelbert Mephu Nguifo
:
Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model. J. Comput. Biol. 23(1): 10-20 (2016) - [c8]Sabeur Aridhi
, Martin Brugnara
, Alberto Montresor
, Yannis Velegrakis
:
Distributed k-core decomposition and maintenance in large dynamic graphs. DEBS 2016: 161-168 - [c7]Sabeur Aridhi
, Alberto Montresor
, Yannis Velegrakis
:
BLADYG: A Novel Block-Centric Framework for the Analysis of Large Dynamic Graphs. HPGP@HPDC 2016: 39-42 - [c6]Chayma Sakouhi, Sabeur Aridhi
, Alessio Guerrieri, Salma Sassi
, Alberto Montresor
:
DynamicDFEP: A Distributed Edge Partitioning Approach for Large Dynamic Graphs. IDEAS 2016: 142-147 - [c5]Nour El Islem Karabadji, Sabeur Aridhi
, Hassina Seridi:
A Closed Frequent Subgraph Mining Algorithm in Unique Edge Label Graphs. MLDM 2016: 43-57 - [i5]Manel Zoghlami, Sabeur Aridhi, Haïtham Sghaier, Mondher Maddouri, Engelbert Mephu Nguifo:
A multiple instance learning approach for sequence data with across bag dependencies. CoRR abs/1602.00163 (2016) - [i4]Sabeur Aridhi, Engelbert Mephu Nguifo:
Big Graph Mining: Frameworks and Techniques. CoRR abs/1602.03072 (2016) - [i3]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Alexander Jung:
Big Data Frameworks: A Comparative Study. CoRR abs/1610.09962 (2016) - [i2]Alexander Jung, Alfred O. Hero III, Alexandru Mara, Sabeur Aridhi:
Scalable Semi-Supervised Learning over Networks using Nonsmooth Convex Optimization. CoRR abs/1611.00714 (2016) - 2015
- [j3]Sabeur Aridhi
, Philippe Lacomme, Libo Ren, Benjamin Vincent:
A MapReduce-based approach for shortest path problem in large-scale networks. Eng. Appl. Artif. Intell. 41: 151-165 (2015) - [j2]Sabeur Aridhi
, Laurent d'Orazio, Mondher Maddouri, Engelbert Mephu Nguifo
:
Density-based data partitioning strategy to approximate large-scale subgraph mining. Inf. Syst. 48: 213-223 (2015) - [c4]Sabeur Aridhi
, Laurent d'Orazio, Mondher Maddouri, Engelbert Mephu Nguifo
:
Cost Models for Distributed Pattern Mining in the Cloud. TrustCom/BigDataSE/ISPA (2) 2015: 112-119 - 2014
- [j1]Sabeur Aridhi, Laurent d'Orazio, Mondher Maddouri, Engelbert Mephu Nguifo:
Un partitionnement basé sur la densité de graphe pour approcher la fouille distribuée de sous-graphes fréquents. Tech. Sci. Informatiques 33(9-10): 711-737 (2014) - [i1]Cyrine Arouri, Engelbert Mephu Nguifo, Sabeur Aridhi, Cécile Roucelle, Gaëlle Bonnet-Loosli, Norbert Tsopzé:
Towards a constructive multilayer perceptron for regression task using non-parametric clustering. A case study of Photo-Z redshift reconstruction. CoRR abs/1412.5513 (2014) - 2013
- [b1]Sabeur Aridhi:
Distributed frequent subgraph mining in the cloud. (Fouille de sous-graphes fréquents dans les nuages). Blaise Pascal University, Clermont-Ferrand, France, 2013 - [c3]Sabeur Aridhi
, Mondher Maddouri, Haïtham Sghaier
, Engelbert Mephu Nguifo
:
Computational phenotype prediction of ionizing-radiation-resistant bacteria with a multiple-instance learning model. BIOKDD 2013: 18-24 - 2012
- [c2]Rabie Saidi
, Sabeur Aridhi
, Engelbert Mephu Nguifo
, Mondher Maddouri:
Feature extraction in protein sequences classification: a new stability measure. BCB 2012: 683-689 - 2010
- [c1]Rabie Saidi, Sabeur Aridhi, Mondher Maddouri, Engelbert Mephu Nguifo:
Etude de stabilité de méthodes d'extraction de motifs à partir des séquences protéiques. EGC 2010: 703-704
Coauthor Index
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