User customization of a word processor
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Configuration agents, control and privacy
CUU '00 Proceedings on the 2000 conference on Universal Usability
Is seeing believing?: how recommender system interfaces affect users' opinions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
The impact of rating scales on user's rating behavior
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Explaining the user experience of recommender systems
User Modeling and User-Adapted Interaction
Evaluating rating scales personality
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
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In web-based adaptive systems, the same rating scales are usually provided to all users for expressing their preferences with respect to various items It emerged from a user experiment that we recently carried out that different users show different preferences with respect to the rating scales to use in the interface of adaptive systems, given the particular topic they are evaluating Starting from this finding, we propose to allow users to choose the kind of rating scale they prefer This approach raises various issues; the most important is that of how an adaptation algorithm can properly deal with values coming from heterogeneous rating scales We conducted an experiment to investigate how users rate the same object on different rating scales On the basis of our interpretation of these results, as an example of one possible solution approach, we propose a three-phase normalization process for mapping preferences expressed with different rating scales onto a unique system representation.