User Evaluation Framework of Recommender Systems
نویسنده
چکیده
This paper explores the evaluation issues of recommender systems particularly from users’ perspective. We first show results of literature surveys on human psychological decision theory and trust building in online environments. Based on the results, we propose an evaluation framework aimed at assessing a recommender’s practical ability in providing decision support benefits to end-users from various aspects. It includes both accuracy/effort measures and a user-trust model of subjective constructs, and a corresponding sample questionnaire design.
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