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International Conference on Artificial Neural Networks

ICANN 2019: Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions pp 456–468Cite as

Evaluation of Tag Clusterings for User Profiling in Movie Recommendation

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 11731)

Abstract

In the web 2.0 era, tags provide an effective mechanism to rapidly annotate and categorize items. However, tags suffer from many problems typically linked to language, like synonymy, polysemy, and ambiguity in general. To overcome this limitation, tag clustering can be used to group tags that represent similar concepts. One of the domains where tag clustering has shown to be particularly useful is the movie recommendation, where tags are used to represent users’ preferences and affinities. In this context it is not yet available a golden standard that can prove the quality of a clustering technique, especially considering that the final aim is the users’ satisfaction rather than an accuracy-like score. To this end, we propose an evaluation criterion for the quality of the resulting clusters based on human judgments.

Keywords

  • Movie recommendation
  • Tag clustering
  • Human judgment
  • Word embeddings

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Notes

  1. 1.

    https://www.themoviedb.org/.

  2. 2.

    http://evexdb.org/pmresources/vec-space-models/.

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Authors and Affiliations

  1. Department of Mathematics, University of Padova, Via Trieste, 63, 35121, Padova, Italy

    Guglielmo Faggioli, Mirko Polato, Ivano Lauriola & Fabio Aiolli

  2. Bruno Kessler Foundation, Via Sommarive, 18, 38123, Trento, Italy

    Ivano Lauriola

Authors
  1. Guglielmo Faggioli
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  2. Mirko Polato
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  3. Ivano Lauriola
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  4. Fabio Aiolli
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Corresponding author

Correspondence to Guglielmo Faggioli .

Editor information

Editors and Affiliations

  1. Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany

    Igor V. Tetko

  2. Institute of Computer Science, Czech Academy of Sciences, Prague 8, Czech Republic

    Dr. Věra Kůrková

  3. Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany

    Pavel Karpov

  4. Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany

    Prof. Fabian Theis

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Faggioli, G., Polato, M., Lauriola, I., Aiolli, F. (2019). Evaluation of Tag Clusterings for User Profiling in Movie Recommendation. In: Tetko, I., Kůrková, V., Karpov, P., Theis, F. (eds) Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions. ICANN 2019. Lecture Notes in Computer Science(), vol 11731. Springer, Cham. https://doi.org/10.1007/978-3-030-30493-5_45

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  • DOI: https://doi.org/10.1007/978-3-030-30493-5_45

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