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Explicable Question Answering

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The Semantic Web: ESWC 2020 Satellite Events (ESWC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12124))

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Abstract

Question answering over Knowledge Graphs has emerged as an intuitive way of querying structured data sources and has witnessed significant progress over the years. However, there is still plenty of space for improvement and there exist specific challenges that are still far from being effectively solved. In this research project, we aim to address some of these challenges and provide innovative solutions in the field. Our research will mainly focus on deep learning approaches such as sequence to sequence models and ranking methods. We plan to contribute to the challenges of explicability and complex queries by further researching the areas and providing resources together with more robust models by using probabilistic methods and meta-learning approaches.

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Notes

  1. 1.

    http://vquanda.sda.tech/.

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Author information

Authors and Affiliations

  1. Smart Data Analytics, University of Bonn, Bonn, Germany

    Endri Kacupaj

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  1. Endri Kacupaj
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Correspondence to Endri Kacupaj .

Editor information

Editors and Affiliations

  1. University of Erlangen-Nuremberg, Nuremberg, Germany

    Andreas Harth

  2. National Research Council, Rome, Italy

    Valentina Presutti

  3. Eurecom, Sophia Antipolis, France

    Raphaël Troncy

  4. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Maribel Acosta

  5. Institute for Information Business at WU Wien, Vienna, Austria

    Axel Polleres

  6. Institute for Information Business at WU Wien, Vienna, Austria

    Javier D. Fernández

  7. Siemens AG Österreich, Vienna, Austria

    Josiane Xavier Parreira

  8. Linköping University, Linköping, Sweden

    Olaf Hartig

  9. Aalborg University, Aalborg, Denmark

    Katja Hose

  10. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Michael Cochez

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Kacupaj, E. (2020). Explicable Question Answering. In: Harth, A., et al. The Semantic Web: ESWC 2020 Satellite Events. ESWC 2020. Lecture Notes in Computer Science(), vol 12124. Springer, Cham. https://doi.org/10.1007/978-3-030-62327-2_41

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  • DOI: https://doi.org/10.1007/978-3-030-62327-2_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62326-5

  • Online ISBN: 978-3-030-62327-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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