Push-Poll Recommender System: Supporting Word of Mouth

  • Andrew Webster
  • Julita Vassileva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4511)


Recommender systems produce social networks as a side effect of predicting what users will like. However, the potential for these social networks to aid in recommending items is largely ignored. We propose a recommender system that works directly with these networks to distribute and recommend items: the informal exchange of information (word of mouth communication) is supported rather than replaced. The paper describes the push-poll approach and evaluates its performance at predicting user ratings for movies against a collaborative filtering algorithm. Overall, the push-poll approach performs significantly better while being computationally efficient and suitable for dynamic domains (e.g. recommending items from RSS feeds).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Andrew Webster
    • 1
  • Julita Vassileva
    • 1
  1. 1.Department of Computer Science, University of Saskatchewan, Saskatoon SK, S7N 5C9Canada

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