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Logic-Based Models for Social Media Retrieval

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Book cover Advances in Information Retrieval (ECIR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11438))

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Abstract

The huge amount of information that is available in social media today has resulted in a pressing demand for information retrieval models to support users in different retrieval tasks in this area. Evaluation of products or services based on other consumers’ reviews are examples of retrieval tasks where users benefit from the information in social media. However, as information in online reviews is provided from different customers, the reviews differ in their degree of credibility. Furthermore, not every detail of a product is reviewed but needs to be taken care when validating a product. Finally, reviews contain contradictions. In this work, we propose a logic-based pipeline to develop a social media retrieval model in which issues of credibility, omissions and contradictions are considered. For modeling these criteria, our approach depends on a probabilistic four-valued logic combined with an open world assumption which employs the unknown knowledge in retrieval tasks.

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Author information

Authors and Affiliations

  1. University of Duisburg-Essen, Duisburg, Germany

    Firas Sabbah

Authors
  1. Firas Sabbah
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Correspondence to Firas Sabbah .

Editor information

Editors and Affiliations

  1. University of Strathclyde, Glasgow, UK

    Leif Azzopardi

  2. Bauhaus Universität Weimar, Weimar, Germany

    Benno Stein

  3. Universität Duisburg-Essen, Duisburg, Germany

    Norbert Fuhr

  4. GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany

    Philipp Mayr

  5. Delft University of Technology, Delft, The Netherlands

    Claudia Hauff

  6. University of Twente, Enschede, The Netherlands

    Djoerd Hiemstra

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Sabbah, F. (2019). Logic-Based Models for Social Media Retrieval. In: Azzopardi, L., Stein, B., Fuhr, N., Mayr, P., Hauff, C., Hiemstra, D. (eds) Advances in Information Retrieval. ECIR 2019. Lecture Notes in Computer Science(), vol 11438. Springer, Cham. https://doi.org/10.1007/978-3-030-15719-7_47

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  • DOI: https://doi.org/10.1007/978-3-030-15719-7_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15718-0

  • Online ISBN: 978-3-030-15719-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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