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User Latent Preference Model for Better Downside Management in Recommender Systems
BibTeX
@MISC{Wang_userlatent,
author = {Jian Wang and Linkedin Corp and David Hardtke and Linkedin Corp},
title = {User Latent Preference Model for Better Downside Management in Recommender Systems},
year = {}
}
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Abstract
Downside management is an important topic in the field of recommender systems. User satisfaction increases when good items are recommended, but satisfaction drops signifi-cantly when bad recommendations are pushed to them. For example, a parent would be disappointed if violent movies are recommended to their kids and may stop using the rec-ommendation system entirely. A vegetarian would feel steak-house recommendations useless. A CEO in a mid-sized com-pany would feel offended by receiving intern-level job recom-mendations. Under circumstances where there is penalty for a bad recommendation, a bad recommendation is worse than no recommendation at all. While most existing work focuses on upside management (recommending the best items to users), this paper emphasizes on achieving better downside
Keyphrases
recommender system better downside management user latent preference model bad recommendation important topic downside management satisfaction drop intern-level job recom-mendations user satisfaction increase rec-ommendation system upside management violent movie good item mid-sized com-pany steak-house recommendation useless work focus
