TY - GEN
T1 - Evaluating rating scales personality
AU - Kuflik, Tsvi
AU - Wecker, Alan J.
AU - Cena, Federica
AU - Gena, Cristina
PY - 2012
Y1 - 2012
N2 - User ratings are a valuable source of information for recommender systems: often, personalized suggestions are generated by predicting the user's preference for an item, based on ratings users explicitly provided for other items. In past experiments that were carried out by us in the gastronomy domain, results showed that rating scales have their own "personality" exerting an influence on user ratings. In this paper, we aim at deepening our knowledge of the effect of rating scale personality on user ratings by taking into account new empirical settings and a different domain (a museum), and partially different rating scales. We compare the results of these new experiments with our previous ones. Our aim is to further validate in a different application context, and domain, and with different rating scales, the fact that rating scales have their own personality which affects users' rating behavior.
AB - User ratings are a valuable source of information for recommender systems: often, personalized suggestions are generated by predicting the user's preference for an item, based on ratings users explicitly provided for other items. In past experiments that were carried out by us in the gastronomy domain, results showed that rating scales have their own "personality" exerting an influence on user ratings. In this paper, we aim at deepening our knowledge of the effect of rating scale personality on user ratings by taking into account new empirical settings and a different domain (a museum), and partially different rating scales. We compare the results of these new experiments with our previous ones. Our aim is to further validate in a different application context, and domain, and with different rating scales, the fact that rating scales have their own personality which affects users' rating behavior.
KW - rating scales
KW - recommender systems
KW - user study
UR - http://www.scopus.com/inward/record.url?scp=84863611792&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-31454-4_27
DO - 10.1007/978-3-642-31454-4_27
M3 - Conference contribution
AN - SCOPUS:84863611792
SN - 9783642314537
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 310
EP - 315
BT - User Modeling, Adaptation, and Personalization - 20th International Conference, UMAP 2012, Proceedings
T2 - 20th International Conference on User Modeling, Adaptation and Personalization, UMAP 2012
Y2 - 16 July 2012 through 20 July 2012
ER -