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20232026
most citedIs More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System

36 citations · 55 across the 20 of their papers we have counts for

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5 papers · 1 filter

cs.IR2025★ 1 cited

Designing and Evaluating an Educational Recommender System with Different Levels of User Control

Qurat Ul Ain, Mohamed Amine Chatti, William Kana Tsoplefack +2

Educational recommender systems (ERSs) play a crucial role in personalizing learning experiences and enhancing educational outcomes by providing recommendations of personalized res…

cs.IR2023★ 2 cited

Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System

Mouadh Guesmi, Mohamed Amine Chatti, Shoeb Joarder +4

Explainable recommender systems (RS) have traditionally followed a one-size-fits-all approach, delivering the same explanation level of detail to each user, without considering the…

cs.IR2023★ 1 cited

Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System

Mouadh Guesmi, Mohamed Amine Chatti, Shoeb Joarder +4

Significant attention has been paid to enhancing recommender systems (RS) with explanation facilities to help users make informed decisions and increase trust in and satisfaction w…

cs.IR2023★ 2 cited

Visualization for Recommendation Explainability: A Survey and New Perspectives

Mohamed Amine Chatti, Mouadh Guesmi, Arham Muslim

Providing system-generated explanations for recommendations represents an important step towards transparent and trustworthy recommender systems. Explainable recommender systems pr…

cs.IR2023★ 1 cited

Trust and Transparency in Recommender Systems

Clara Siepmann, Mohamed Amine Chatti

Trust is long recognized to be an important factor in Recommender Systems (RS). However, there are different perspectives on trust and different ways to evaluate it. Moreover, a li…