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POPPONENT: Highly accurate, individually and socially efficient opponent preference model in bilateral multi issue negotiations (Extended Abstract)., и . IJCAI, стр. 5100-5104. ijcai.org, (2017)POPPONENT: Highly accurate, individually and socially efficient opponent preference model in bilateral multi issue negotiations., и . Artif. Intell., (2016)Modelling and Analysis of Temporal Preference Drifts Using A Component-Based Factorised Latent Approach., , и . CoRR, (2018)ReEx: An integrated architecture for preference model representation and explanation., , и . Expert Syst. Appl., (2020)BraveCat: Iterative Deepening Distance-Based Opponent Modeling and Hybrid Bidding in Nonlinear Ultra Large Bilateral Multi Issue Negotiation Domains., и . ANAC@AAMAS, том 638 из Studies in Computational Intelligence, стр. 285-293. Springer, (2014)Imbalanced Data Sparsity as a Source of Unfair Bias in Collaborative Filtering., , , , , , и . RecSys, стр. 531-533. ACM, (2022)Modelling socially-influenced conditional preferences over feature values in recommender systems based on factorised collaborative filtering., и . Expert Syst. Appl., (2017)Modelling and analysis of temporal preference drifts using a component-based factorised latent approach., , и . Expert Syst. Appl., (2019)Proposing a Highly Accurate Hybrid Component-Based Factorised Preference Model in Recommender Systems., , и . IJCAI, стр. 1332-1339. ijcai.org, (2017)Offline Evaluation Standards for Recommender Systems., , , , , и . RecSys, стр. 567-568. ACM, (2021)