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Explainable Recommender Systems with Knowledge Graphs and Language Models

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Advances in Information Retrieval (ECIR 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14612))

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Abstract

In this tutorial, we delve into recent advances in explainable recommendation using Knowledge Graphs (KGs). The session begins by introducing the fundamental principles behind the increasing adoption of KGs in modern recommender systems. Then, the tutorial explores recent techniques that leverage KGs as an input for language models tailored to explainable recommendation, describing also data types, methods, and evaluation protocols and metrics. Conceptual elements are complemented with hands-on sessions, providing practical implementations using open-source tools and public datasets. Concluding with a comprehensive case study in the education domain as a recap, the tutorial analyses emerging issues and outlines prospective trajectories in this field. The tutorial website is available at https://explainablerecsys.github.io/ecir2024/.

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Acknowledgement

We acknowledge financial support under the National Recovery and Resilience Plan (NRRP), Miss. 4 Comp. 2 Inv. 1.5 - Call for tender No.3277 published on Dec 30, 2021 by the Italian Ministry of University and Research (MUR) funded by the European Union - NextGenerationEU. Prj. Code ECS0000038 eINS Ecosystem of Innovation for Next Generation Sardinia, CUP F53C22000430001, Grant Assignment Decree N. 1056, Jun 23, 2022 by the MUR.

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Authors and Affiliations

  1. University of Cagliari, Cagliari, Italy

    Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Francesca Maridina Malloci & Mirko Marras

Authors
  1. Giacomo Balloccu
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  2. Ludovico Boratto
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  3. Gianni Fenu
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  4. Francesca Maridina Malloci
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  5. Mirko Marras
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Corresponding author

Correspondence to Mirko Marras .

Editor information

Editors and Affiliations

  1. Georgetown University, Washington, WA, USA

    Nazli Goharian

  2. University of Pisa, PISA, Pisa, Italy

    Nicola Tonellotto

  3. King's College London, London, UK

    Yulan He

  4. University College London, London, UK

    Aldo Lipani

  5. University of Glasgow, Glasgow, UK

    Graham McDonald

  6. University of Glasgow, Glasgow, UK

    Craig Macdonald

  7. University of Glasgow, Glasgow, UK

    Iadh Ounis

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Balloccu, G., Boratto, L., Fenu, G., Malloci, F.M., Marras, M. (2024). Explainable Recommender Systems with Knowledge Graphs and Language Models. In: Goharian, N., et al. Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14612. Springer, Cham. https://doi.org/10.1007/978-3-031-56069-9_46

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  • DOI: https://doi.org/10.1007/978-3-031-56069-9_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56068-2

  • Online ISBN: 978-3-031-56069-9

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