The field of recommender systems has seen substantial progress in recent years in terms of algorithmic sophistica- tion and quality of recommendations as ...
Feb 27, 2018 · Such user-generated content can serve as a useful source for deriving explanatory information that may increase the user's understanding of the ...
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In this paper, we describe a set of developments we undertook to couple such textual content with common recommender techniques. These developments have moved ...
Jan 15, 2021 · Providing explanations based on user reviews in recommender systems (RS) may increase users' perception of transparency or effectiveness.
Mar 17, 2020 · We propose a recommendation and explanation method that exploits the comprehensiveness of textual data to make the underlying criteria and mechanisms that lead ...
Abstract. Explaining recommendations helps users to make better, more satisfying decisions. We describe a novel approach to explanation for rec-.
Jan 25, 2023 · Besides similarity, some recommendation explanations include content information (e.g., attributes and reviews) of items in recommender systems ...
Jul 1, 2020 · Review texts constitute a valuable source for making system-generated recommendations both more accurate and more transparent.
May 14, 2024 · In this paper, we provide a comprehensive overview of the developments in review-based recommender systems over recent years.
There are different ways in which a user can give feedback to the system to let it know how it is doing. Here we expand on four ways suggested by (Ginty and ...