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Offline Evaluation

  • Leandro Balby MarinhoEmail author
  • Andreas Hotho
  • Robert Jäschke
  • Alexandros Nanopoulos
  • Steffen Rendle
  • Lars Schmidt-Thieme
  • Gerd Stumme
  • Panagiotis Symeonidis
Chapter
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

In this chapter we present the most usual experimental protocols and metrics employed for offline evaluation of tag recommender systems. By offline we mean that the algorithms are evaluated on a snapshot of some real-world STS dataset, which, in turn, is typically split into training and test datasets. This corresponds to the most typical evaluation scenario found in the literature since researchers do not need to have a STS up and running for assessing the performance of his/her algorithms. We also summarize the main tag recommendation algorithms presented in this book, pointing out pros and cons in terms of the metrics and protocols introduced in this chapter.

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Copyright information

© The Author(s) 2012

Authors and Affiliations

  • Leandro Balby Marinho
    • 1
    Email author
  • Andreas Hotho
    • 2
  • Robert Jäschke
    • 3
  • Alexandros Nanopoulos
    • 4
  • Steffen Rendle
    • 5
  • Lars Schmidt-Thieme
    • 4
  • Gerd Stumme
    • 3
  • Panagiotis Symeonidis
    • 6
  1. 1.Federal University of Campina GrandeCampina GrandeBrazil
  2. 2.University of WürzburgWürzburgGermany
  3. 3.University of KasselKasselGermany
  4. 4.University of HildesheimHildesheimGermany
  5. 5.University of KonstanzKonstanzGermany
  6. 6.Aristotle UniversityThessalonikiGreece

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