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Farhad Zafari
Farhad Zafari
SEEK Limited
Verified email at seek.com.au
Title
Cited by
Cited by
Year
Popponent: Highly accurate, individually and socially efficient opponent preference model in bilateral multi issue negotiations
F Zafari, F Nassiri-Mofakham
Artificial Intelligence 237, 59-91, 2016
342016
Modelling and analysis of temporal preference drifts using a component-based factorised latent approach
F Zafari, I Moser, T Baarslag
Expert systems with applications 116, 186-208, 2019
262019
Modelling socially-influenced conditional preferences over feature values in recommender systems based on factorised collaborative filtering
F Zafari, I Moser
Expert Systems with Applications 87, 98-117, 2017
172017
Dopponent: A socially efficient preference model of opponent in bilateral multi issue negotiations
F Zafari, MF NASSIRI, HALI ZEINAL
JOURNAL OF COMPUTING AND SECURITY 1 (4), 283-292, 2014
122014
Bravecat: iterative deepening distance-based opponent modeling and hybrid bidding in nonlinear ultra large bilateral multi issue negotiation domains
F Zafari, F Nassiri-Mofakham
Recent Advances in Agent-based Complex Automated Negotiation, 285-293, 2016
112016
Proposing a Highly Accurate Hybrid Component-Based Factorised Preference Model in Recommender Systems.
F Zafari, R Rahmani, I Moser
IJCAI, 1332-1339, 2017
72017
Feature-aware factorised collaborative filtering
F Zafari, I Moser
AI 2016: Advances in Artificial Intelligence: 29th Australasian Joint …, 2016
52016
Imbalanced data sparsity as a source of unfair bias in collaborative filtering
A Joshi, CL Wong, D Marinho de Oliveira, F Zafari, F Mourao, S Ribas, ...
Proceedings of the 16th ACM Conference on Recommender Systems, 531-533, 2022
12022
Offline Evaluation Standards for Recommender Systems
CL Wong, D De Oliveira, F Zafari, F Mourão, R Colares, S Ribas
Proceedings of the 15th ACM Conference on Recommender Systems, 567-568, 2021
12021
ReEx: An Integrated Architecture for Preference Model Representation and Explanation
F Zafari, I Moser, T Sellis
Expert Systems With Applications, 2020
12020
Accurate, efficient, and explainable modelling of context-dependent preferences using matrix factorisation
F Zafari
PhD Thesis, 2019
2019
Geno-Fuzzy Segmentation Approach to Improve the Profitability of Marketing Campaigns in Banking Industry
Farhad Zafari, Faria Nassiri Mofakham, Reza Hosseini Pour
Proceedings of 19th Annual conference of Computer Society of Iran, Tehran …, 2014
2014
Elicitation of User Preferences in Automated Multi-agent Negotiations
MA Rigi, F Zafari, I Moser
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Articles 1–13