Learning argumentative recommenders. Cailloux, O. 2018. DA2PL'2018: From Multiple Criteria Decision Aid to Preference Learning
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Conference Hal Slides abstract bibtex
Article Conference Hal Slides abstract bibtex 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: 0
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