Learning argumentative recommenders. Cailloux, O. 2018. DA2PL'2018: From Multiple Criteria Decision Aid to Preference Learning
Article
Conference
Hal
Slides abstract bibtex 12 downloads Recommender systems aim at recommending some item as most appropriate for the user. This article introduces a new way of measuring appropriateness for the user: an item is among the most appropriate ones if it is among the preferred items of the user when considering all arguments in favor or against all possible items. I describe precisely this goal and describe what a recommender system aiming for that goal could look like, called an Argumentative Recommender. I also provide a way of measuring whether a recommender system has achieved the goal, which can be used to compare such recommender systems, and briefly outline a way of building such a system.
@misc{cailloux_learning_2018,
title = {Learning argumentative recommenders},
keywords = {Deliberated judgment, Preference modeling},
url_Article = {https://da2pl.cs.put.poznan.pl/programme/detailed-programme/da2pl2018-abstract-09.pdf},
url_Conference = {https://da2pl.cs.put.poznan.pl/programme/detailed-programme},
url_HAL = {https://hal.science/hal-04176648},
url_Slides = {https://da2pl.cs.put.poznan.pl/programme/detailed-programme/da2pl2018-slides-15.pdf},
abstract = {Recommender systems aim at recommending some item as most appropriate for the user. This article introduces a new way of measuring appropriateness for the user: an item is among the most appropriate ones if it is among the preferred items of the user when considering all arguments in favor or against all possible items. I describe precisely this goal and describe what a recommender system aiming for that goal could look like, called an Argumentative Recommender. I also provide a way of measuring whether a recommender system has achieved the goal, which can be used to compare such recommender systems, and briefly outline a way of building such a system.},
note = {DA2PL'2018: From Multiple Criteria Decision Aid to Preference Learning},
author = {Cailloux, Olivier},
year = {2018}
}
Downloads: 12
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