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Cold Start Problem: A Lightweight Approach

  • Leo Iaquinta
  • Giovanni Semeraro
  • Pasquale Lops
Part of the Studies in Computational Intelligence book series (SCI, volume 439)

Abstract

The chapter presents the SWAPTeam participation at the ECML/PKDD 2011 - Discovery Challenge for the task on the cold start problem focused on making recommendations for new video lectures. The developed solution uses a content-based approach because it is less sensitive to the cold start problem that is commonly associated with pure collaborative filtering recommenders. The Challenge organizers encouraged solutions that can actually affect VideoLecture.net, thus the proposed integration strategy is the hybridization by switching. In addition, the surrounding idea for the proposed solution is that providing recommendations about cold items remains a chancy task, thus a computational resource curtailment for such task is a reasonable strategy to control performance trade-off of a day-to-day running system. The main contribution concerns about the compromise between recommendation accuracy and scalability performance of proposed approach.

Keywords

Recommender System Cold Start Learning Step Cold Start Problem Challenge Organizer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Leo Iaquinta
    • 1
  • Giovanni Semeraro
    • 2
  • Pasquale Lops
    • 2
  1. 1.University of Milano–BicoccaMilanoItaly
  2. 2.University of Bari “Aldo Moro”BariItaly

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