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@inproceedings{Rago:2018:ijcai.2018/269,
author = {Rago, A and Cocarascu, O and Toni, F},
doi = {ijcai.2018/269},
pages = {1949--1955},
title = {Argumentation-based recommendations: fantastic explanations and how to find them},
url = {http://dx.doi.org/10.24963/ijcai.2018/269},
year = {2018}
}

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TY  - CPAPER
AB  - A significant problem of recommender systems is their inability to explain recommendations, resulting in turn in ineffective feedback from users and the inability to adapt to users’ preferences. We propose a hybrid method for calculating predicted ratings, built upon an item/aspect-based graph with users’ partially given ratings, that can be naturally used to provide explanations for recommendations, extracted from user-tailored Tripolar Argumentation Frameworks (TFs). We show that our method can be understood as a gradual semantics for TFs, exhibiting a desirable, albeit weak, property of balance. We also show experimentally that our method is competitive in generating correct predictions, compared with state-of-the-art methods, and illustrate how users can interact with the generated explanations to improve quality of recommendations.
AU  - Rago,A
AU  - Cocarascu,O
AU  - Toni,F
DO  - ijcai.2018/269
EP  - 1955
PY  - 2018///
SP  - 1949
TI  - Argumentation-based recommendations: fantastic explanations and how to find them
UR  - http://dx.doi.org/10.24963/ijcai.2018/269
UR  - http://hdl.handle.net/10044/1/63574
ER  -

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