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International Conference on User Modeling, Adaptation, and Personalization

UMAP 2015: User Modeling, Adaptation and Personalization pp 331-336 | Cite as

News Recommender Based on Rich Feedback

  • Liliana Ardissono
  • Giovanna Petrone
  • Francesco Vigliaturo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9146)

Abstract

This paper proposes to exploit author-defined tags and social interaction data (commenting and sharing news items) in news recommendation. Moreover it presents a hybrid news recommender which suggest news items on the basis of the reader’s short and long-term reading history, taking reading trends and short-term interests into account. The experimental results we carried out provided encouraging results about the accuracy of the recommendations.

Keywords

Hybrid news recommender Tag-based news specification 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Liliana Ardissono
    • 1
  • Giovanna Petrone
    • 1
  • Francesco Vigliaturo
    • 1
  1. 1.Dipartimento di InformaticaUniversità di TorinoTurinItaly

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