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A Transparent Logical Framework for Aspect-Oriented Product Ranking Based on User Reviews

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Advances in Information Retrieval (ECIR 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12656))

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Abstract

Customer reviews play a major role in online shopping, but there is hardly any support for aggregating the opinions of multiple reviewers, especially when the user is interested in certain aspects only. Current retrieval methods cannot handle the issues of limited credibility, contradictions and information omission when dealing with this type of documents. For addressing these problems, we investigate two multi-valued logic retrieval models. Subjective logic was specifically developed for considering uncertainty and subjective opinions. As an alternative, we regard a probabilistic version of a 4-valued logic addressing missing and inconsistent information. For an aspect-product pair, we get a probability distribution over the truth values and use them for ranking the search results. Our experimental results on a data set from the hotel domain show that our proposed approaches outperform the traditional keyword-based methods for the task of ranking items based on reviews. Moreover, the logic-based methods are more transparent than other approaches.

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Notes

  1. 1.

    A path here is the combination of one truth value from each review.

  2. 2.

    https://partner.booking.com/en-us/help/guest-reviews/what-are-guest-reviews-and-who-can-write-one, last accessed on Sep. 10th 2020.

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Acknowledgements

This work was supported by the German Research Foundation (DFG) under grant No. GRK 2167, Research Training Group “User-Centred Social Media”.

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Authors and Affiliations

  1. University of Duisburg-Essen, Duisburg, Germany

    Firas Sabbah & Norbert Fuhr

Authors
  1. Firas Sabbah
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  2. Norbert Fuhr
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Corresponding author

Correspondence to Firas Sabbah .

Editor information

Editors and Affiliations

  1. Radboud University Nijmegen, Nijmegen, The Netherlands

    Djoerd Hiemstra

  2. Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium

    Marie-Francine Moens

  3. Toulouse Institute of Computer Science Research, Toulouse, France

    Josiane Mothe

  4. Istituto di Scienza e Tecnologie dell’Informazione, Consiglio Nazionale delle Ricerche, Pisa, Italy

    Raffaele Perego

  5. Leipzig University, Leipzig, Germany

    Martin Potthast

  6. Istituto di Scienza e Tecnologie dell’Informazione, Consiglio Nazionale delle Ricerche, Pisa, Italy

    Fabrizio Sebastiani

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Sabbah, F., Fuhr, N. (2021). A Transparent Logical Framework for Aspect-Oriented Product Ranking Based on User Reviews. In: Hiemstra, D., Moens, MF., Mothe, J., Perego, R., Potthast, M., Sebastiani, F. (eds) Advances in Information Retrieval. ECIR 2021. Lecture Notes in Computer Science(), vol 12656. Springer, Cham. https://doi.org/10.1007/978-3-030-72113-8_37

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  • DOI: https://doi.org/10.1007/978-3-030-72113-8_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72112-1

  • Online ISBN: 978-3-030-72113-8

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