@inproceedings{b82fbced96404065a7f637fe8fa0f15f,
title = "Expanding controllability of hybrid recommender systems: From positive to negative relevance",
abstract = "A hybrid recommender system fuses multiple data sources, usually with static and nonadjustable weightings, to deliver recommendations. One limitation of this approach is the problem to match user preference in all situations. In this paper, we present two user-controllable hybrid recommender interfaces, which offer a set of sliders to dynamically tune the impact of different sources of relevance on the final ranking. Two user studies were performed to design and evaluate the proposed interfaces.",
author = "Behnam Rahdari and Tsai, {Chun Hua} and Peter Brusilovsky",
note = "Publisher Copyright: {\textcopyright} 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 32nd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2019 ; Conference date: 19-05-2019 Through 22-05-2019",
year = "2019",
language = "English (US)",
series = "Proceedings of the 32nd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2019",
publisher = "The AAAI Press",
pages = "431--434",
editor = "Roman Bartak and Keith Brawner",
booktitle = "Proceedings of the 32nd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2019",
}