FReSET: an evaluation framework for folksonomy-based recommender systems

  • Authors:
  • Renato Domínguez García;Matthias Bender;Mojisola Anjorin;Christoph Rensing;Ralf Steinmetz

  • Affiliations:
  • TU Darmstadt, Darmstadt, Germany;TU Darmstadt, Darmstadt, Germany;TU Darmstadt, Darmstadt, Germany;TU Darmstadt, Darmstadt, Germany;TU Darmstadt, Darmstadt, Germany

  • Venue:
  • Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
  • Year:
  • 2012

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Abstract

FReSET is a new recommender systems evaluation framework aiming to support research on folksonomy-based recommender systems. It provides interfaces for the implementation of folksonomy-based recommender systems and supports the consistent and reproducible offline evaluations on historical data. Unlike other recommender systems framework projects, the emphasis here is on providing a flexible framework allowing users to implement their own folksonomy-based recommender algorithms and pre-processing filtering methods rather than just providing a collection of collaborative filtering implementations. FReSET includes a graphical interface for result visualization and different cross-validation implementations to complement the basic functionality.