| A hybrid multi-criteria recommender system using ontology and neuro-fuzzy techniques NR Kermany, SH Alizadeh Electronic Commerce Research and Applications 21, 50-64, 2017 | 86 | 2017 |
| An ethical multi-stakeholder recommender system based on evolutionary multi-objective optimization NR Kermany, W Zhao, J Yang, J Wu, L Pizzato 2020 IEEE International Conference on Services Computing (SCC), 478-480, 2020 | 7 | 2020 |
| Reincre: Enhancing collaborative filtering recommendations by incorporating user rating credibility NR Kermany, W Zhao, J Yang, J Wu International Conference on Web Information Systems Engineering, 64-72, 2020 | 3 | 2020 |
| A fuzzy recommender system for forecasting customer segmentation by multi-variable fuzzy rule interpolation NR Kermany, SH Alizadeh 2013 13th Iranian Conference on Fuzzy Systems (IFSC), 1-5, 2013 | 2 | 2013 |
| A New Model for Best Customer Segment Selection Using Fuzzy TOPSIS Based on Shannon Entropy N Ranjbar Kermany, S H Alizadeh Journal of Computer & Robotics 5 (2), 7-12, 2012 | 2 | 2012 |
| A fairness-aware multi-stakeholder recommender system N Ranjbar Kermany, W Zhao, J Yang, J Wu, L Pizzato World Wide Web 24 (6), 1995-2018, 2021 | 1 | 2021 |
| Fair-SRS: A Fair Session-based Recommendation System N Ranjbar Kermany, J Yang, J Wu, L Pizzato Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | | 2022 |
| Incorporating user rating credibility in recommender systems NR Kermany Sydney, Australia: Macquarie University, 2019 | | 2019 |
Sasan AlizadehIRAN Telecommunication Research CenterVerified email at itrc.ac.ir
