Inproceedings,

Explainable Recommendation for Repeat Consumption

, and .
Fourteenth ACM Conference on Recommender Systems, page 462-467. ACM, (September 2020)
DOI: 10.1145/3383313.3412230

Abstract

Displaying appropriate explanations for recommended items is of vital importance for improving the persuasiveness and user satisfaction of recommender systems. Although a user often consumes the same item repeatedly in some domains such as music and restaurants, existing studies have focused on generating explanations for recommending novel items. In this paper, we describe the concept of explainable recommendation for repeatedly consumed items. Because of the high proportion of repeat consumption in music listening, we suggest nine kinds of explanations for song recommendations according to three factors: personal, social, and item factors. From the results of an online survey involving 622 participants, we evaluate the usefulness of these explanations.

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