As showed in a previous work, different users show different preferences with respect to the rating scales to use for evaluating items in recommender systems. Thus in order to promote users' participation and satisfaction with recommender systems, we propose to allow users to choose the rating scales to use. Thus, recommender systems should be able to deal with ratings coming from heterogeneous scales in order to produce correct recommendations. In this paper we present two user studies that investigate the role of rating scales on user's rating behavior, showing that the rating scales have their own "personality" and mathematical normalization is not enough to cope with mapping among different rating scales. © 2011 Springer-Verlag.
CITATION STYLE
Gena, C., Brogi, R., Cena, F., & Vernero, F. (2011). The impact of rating scales on user’s rating behavior. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6787 LNCS, pp. 123–134). https://doi.org/10.1007/978-3-642-22362-4_11
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