Personalized explanations for hybrid recommender systems

@article{Kouki2019PersonalizedEF,
  title={Personalized explanations for hybrid recommender systems},
  author={Pigi Kouki and James Schaffer and J. Pujara and J. O'Donovan and L. Getoor},
  journal={Proceedings of the 24th International Conference on Intelligent User Interfaces},
  year={2019}
}
  • Pigi Kouki, James Schaffer, +2 authors L. Getoor
  • Published 2019
  • Computer Science
  • Proceedings of the 24th International Conference on Intelligent User Interfaces
  • Recommender systems have become pervasive on the web, shaping the way users see information and thus the decisions they make. [...] Key Method We experiment with 1) different explanation styles (e.g., user-based, item-based), 2) manipulating the number of explanation styles presented, and 3) manipulating the presentation format (e.g., textual vs. visual). We apply a mixed model statistical analysis to consider user personality traits as a control variable and demonstrate the usefulness of our approach in…Expand Abstract
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    References

    SHOWING 1-4 OF 4 REFERENCES
    Collaborative Filtering for Implicit Feedback Datasets
    • 2,239
    • Highly Influential
    • PDF
    Explaining collaborative filtering recommendations
    • 1,501
    • Highly Influential
    • PDF
    How to Recommend?: User Trust Factors in Movie Recommender Systems
    • 40
    • Highly Influential
    Structural equation modeling. Wiley Online Library
    • 2003