Folgen
Seyed Mohssen Ghafari
Seyed Mohssen Ghafari
Bestätigte E-Mail-Adresse bei students.mq.edu.au
Titel
Zitiert von
Zitiert von
Jahr
Bee-MMT: A load balancing method for power consumption management in cloud computing
SM Ghafari, M Fazeli, A Patooghy, L Rikhtechi
2013 Sixth International Conference on Contemporary Computing (IC3), 76-80, 2013
592013
Proposing a load balancing method based on Cuckoo Optimization Algorithm for energy management in cloud computing infrastructures
M Yakhchi, SM Ghafari, S Yakhchi, M Fazeli, A Patooghi
2015 6th International Conference on Modeling, Simulation, and Applied …, 2015
502015
Towards cognitive recommender systems
A Beheshti, S Yakhchi, S Mousaeirad, SM Ghafari, SR Goluguri, MA Edrisi
Algorithms 13 (8), 176, 2020
462020
A survey on association rules mining using heuristics
SM Ghafari, C Tjortjis
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1307, 2019
352019
personality2vec: Enabling the Analysis of Behavioral Disorders in Social Networks
A Beheshti, V Moraveji-Hashemi, S Yakhchi, HR Motahari-Nezhad, ...
Proceedings of the 13th International Conference on Web Search and Data …, 2020
322020
ICA-MMT: A load balancing method in cloud computing environment
S Yakhchi, SM Ghafari, M Yakhchi, M Fazeli, A Patooghy
2015 2nd World Symposium on Web Applications and Networking (WSWAN), 1-7, 2015
322015
Enabling the Analysis of Personality Aspects in Recommender Systems
S Yakhchi, A Beheshti, SM Ghafari, M Orgun
26th Pacific Asia Conference on Information Systems (PACIS), Xian, China, 2019
272019
Social context-aware trust prediction: methods for identifying fake news
SM Ghafari, S Yakhchi, A Beheshti, M Orgun
International Conference on Web Information Systems Engineering, 161-177, 2018
252018
A survey on trust prediction in online social networks
SM Ghafari, A Beheshti, A Joshi, C Paris, A Mahmood, S Yakhchi, ...
IEEE Access 8, 144292-144309, 2020
212020
SETTRUST: social exchange theory based context-aware trust prediction in online social networks
SM Ghafari, S Yakhchi, A Beheshti, M Orgun
International workshop on data quality and trust in big data, 46-61, 2018
182018
CNR: cross-network recommendation embedding user’s personality
S Yakhchi, SM Ghafari, A Beheshti
International Workshop on Data Quality and Trust in Big Data, 62-77, 2018
162018
Towards a deep attention-based sequential recommender system
S Yakhchi, A Beheshti, SM Ghafari, MA Orgun, G Liu
IEEE Access 8, 178073-178084, 2020
142020
DCAT: A Deep Context-Aware Trust Prediction Approach for Online Social Networks
MO Seyed Mohssen Ghafari, Aditya Joshi, Amin Beheshti, Cecile Paris, Shahpar ...
Proceedings of the 17th International Conference on Advances in Mobile …, 2019
14*2019
ARMICA-improved: a new approach for association rule mining
S Yakhchi, SM Ghafari, C Tjortjis, M Fazeli
International Conference on Knowledge Science, Engineering and Management …, 2017
142017
Association rules mining by improving the imperialism competitive algorithm (ARMICA)
SM Ghafari, C Tjortjis
IFIP International Conference on Artificial Intelligence Applications and …, 2016
82016
A Dynamic Deep Trust Prediction Approach for Online Social Networks
SM Ghafari, A Beheshti, A Joshi, C Paris, S Yakhchi, A Jolfaei, MA Orgun
The 18th International Conference on Advances in Mobile Computing …, 2020
62020
A convolutional attention network for unifying general and sequential recommenders
S Yakhchi, A Behehsti, S Ghafari, I Razzak, M Orgun, M Elahi
Information Processing & Management 59 (1), 102755, 2022
52022
An Intelligent System for Multi-topic Social Spam Detection in Microblogging
B Abu-Salih, DA Qudah, M Al-Hassan, SM Ghafari, T Issa, I Aljarah, ...
arXiv preprint arXiv:2201.05203, 2022
42022
Towards time-aware context-aware deep trust prediction in online social networks
SM Ghafari
arXiv preprint arXiv:2003.09543, 2020
32020
TAP: A two-level trust and personality-aware recommender system
S Yakhchi, SM Ghafari, M Orgun
International Conference on Service-Oriented Computing, 294-308, 2020
22020
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20