Explaining User Models with Different Levels of Detail for Transparent Recommendation: A User Study

Mouadh Guesmi, Mohamed Amine Chatti, Laura Vorgerd, Thao Ngo, Shoeb Ahmed Joarder, Qurat Ul Ain, Arham Muslim
2022 User Modeling, Adaptation, and Personalization  
In this paper, we shed light on explaining user models for transparent recommendation while considering user personal characteristics. To this end, we developed a transparent Recommendation and Interest Modeling Application (RIMA) that provides interactive, layered explanations of the user model with three levels of detail (basic, intermediate, advanced) to meet the demands of different types of end-users. We conducted a within-subject study (N=31) to investigate the relationship between
more » ... l characteristics and the explanation level of detail, and the effects of these two variables on the perception of the explainable recommender system with regard to different explanation goals. Based on the study results, we provided some suggestions to support the effective design of user model explanations for transparent recommendation. CCS CONCEPTS • Human-centered computing → Interactive systems and tools; • Computing methodologies → Artificial intelligence.
doi:10.1145/3511047.3537685 dblp:conf/um/GuesmiCVNJAM22 fatcat:rlytcck3rzhyrb7yygp3jmui2i