Evaluating rating scales personality

Tsvi Kuflik, Alan J. Wecker, Federica Cena, Cristina Gena

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationUser Modeling, Adaptation, and Personalization - 20th International Conference, UMAP 2012, Proceedings
Pages310-315
Number of pages6
DOIs
StatePublished - 2012
Event20th International Conference on User Modeling, Adaptation and Personalization, UMAP 2012 - Montreal, QC, Canada
Duration: 16 Jul 201220 Jul 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7379 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on User Modeling, Adaptation and Personalization, UMAP 2012
Country/TerritoryCanada
CityMontreal, QC
Period16/07/1220/07/12

Keywords

  • rating scales
  • recommender systems
  • user study

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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