Sabeur Aridhi

According to our database1, Sabeur Aridhi authored at least 26 papers between 2010 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




Special issue on "Uncertainty in Cloud Computing: Concepts, Challenges and Current Solutions".
Int. J. Approx. Reasoning, 2019

A data sampling and attribute selection strategy for improving decision tree construction.
Expert Syst. Appl., 2019

The uncertain cloud: State of the art and research challenges.
Int. J. Approx. Reasoning, 2018

An experimental survey on big data frameworks.
Future Generation Comp. Syst., 2018

Improving memory-based user collaborative filtering with evolutionary multi-objective optimization.
Expert Syst. Appl., 2018

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), 2018

ABClass : Une approche d'apprentissage multi-instances pour les séquences(ABClass: A multiple instance learning approach for sequence data).
Proceedings of the Actes de la Conférence Nationale d'Intelligence Artificielle et Rencontres des Jeunes Chercheurs en Intelligence Artificielle (CNIA+RJCIA 2018), 2018

Exploiting Complex Protein Domain Networks for Protein Function Annotation.
Proceedings of the Complex Networks and Their Applications VII, 2018

An evolutionary scheme for decision tree construction.
Knowl.-Based Syst., 2017

MR-SimLab: Scalable subgraph selection with label similarity for big data.
Inf. Syst., 2017

BLADYG: A Graph Processing Framework for Large Dynamic Graphs.
Big Data Research, 2017

A Distributed Framework for Large-Scale Time-Dependent Graph Analysis.
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), 2017

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.
Journal of Computational Biology, 2016

Big Graph Mining: Frameworks and Techniques.
Big Data Research, 2016

A Closed Frequent Subgraph Mining Algorithm in Unique Edge Label Graphs.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2016

DynamicDFEP: A Distributed Edge Partitioning Approach for Large Dynamic Graphs.
Proceedings of the 20th International Database Engineering & Applications Symposium, 2016

BLADYG: A Novel Block-Centric Framework for the Analysis of Large Dynamic Graphs.
Proceedings of the ACM Workshop on High Performance Graph Processing, 2016

Distributed k-core decomposition and maintenance in large dynamic graphs.
Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, 2016

Density-based data partitioning strategy to approximate large-scale subgraph mining.
Inf. Syst., 2015

A MapReduce-based approach for shortest path problem in large-scale networks.
Eng. Appl. of AI, 2015

Cost Models for Distributed Pattern Mining in the Cloud.
Proceedings of the 2015 IEEE TrustCom/BigDataSE/ISPA, 2015

Un partitionnement basé sur la densité de graphe pour approcher la fouille distribuée de sous-graphes fréquents.
Technique et Science Informatiques, 2014

Distributed frequent subgraph mining in the cloud. (Fouille de sous-graphes fréquents dans les nuages).
PhD thesis, 2013

Computational phenotype prediction of ionizing-radiation-resistant bacteria with a multiple-instance learning model.
Proceedings of the 12th International Workshop on Data Mining in Bioinformatics, 2013

Feature extraction in protein sequences classification: a new stability measure.
Proceedings of the ACM International Conference on Bioinformatics, 2012

Etude de stabilité de méthodes d'extraction de motifs à partir des séquences protéiques.
Proceedings of the Extraction et gestion des connaissances (EGC'2010), 2010