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2020 – today
- 2021
[j4]Imadeddine Mountasser, Brahim Ouhbi, Ferdaous Hdioud, Bouchra Frikh
:
Semantic-based Big Data integration framework using scalable distributed ontology matching strategy. Distributed Parallel Databases 39(4): 891-937 (2021)- 2020
- [j3]Imadeddine Mountasser, Brahim Ouhbi, Bouchra Frikh, Ferdaous Hdioud:
Big Data Research in the Tourism Industry: Requirements and Challenges. Int. J. Mob. Comput. Multim. Commun. 11(4): 26-41 (2020)
2010 – 2019
- 2018
- [j2]Ferdaous Hdioud, Bouchra Frikh, Brahim Ouhbi, Imadeddine Mountasser, Asmaa Benghabrit:
Recommendation using a clustering algorithm based on a hybrid features selection method. J. Intell. Inf. Syst. 51(1): 183-205 (2018) - 2017
- [b1]Ferdaous Hdioud:
Industrial Recommendation Systems in Big Data Context: Efficient Solutions for Cold- Start issues. (Les systèmes de recommandations industrielles dans un contexte du Big Data: des solutions efficaces pour le problèmes de démarrage à froid). Sidi Mohamed Ben Abdellah University, Morocco, 2017 - [j1]Ferdaous Hdioud, Bouchra Frikh, Brahim Ouhbi, Ismail Khalil:
Multi-Criteria Recommender Systems: A Survey and a Method to Learn New User's Profile. Int. J. Mob. Comput. Multim. Commun. 8(4): 20-48 (2017) - 2015
- [c3]Ferdaous Hdioud, Bouchra Frikh, Asmaa Benghabrit, Brahim Ouhbi:
Collaborative Filtering with Hybrid Clustering Integrated Method to Address New-Item Cold-Start Problem. IDC 2015: 285-296 - 2013
- [c2]Ferdaous Hdioud, Bouchra Frikh, Brahim Ouhbi:
Multi-Criteria Recommender Systems based on Multi-Attribute Decision Making. iiWAS 2013: 203 - 2012
- [c1]Ferdaous Hdioud, Bouchra Frikh, Brahim Ouhbi:
A comparison study of some algorithms in Recommender Systems. CIST 2012: 130-135
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