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On Enhancing Visual Query Building over KGs Using Query Logs

  • Vidar KlungreEmail author
  • Ahmet Soylu
  • Martin Giese
  • Arild Waaler
  • Evgeny Kharlamov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11341)

Abstract

Knowledge Graphs have recently gained a lot of attention and have been successfully applied in both academia and industry. Since KGs may be very large: they may contain millions of entities and triples relating them to each other, to classes, and assigning them data values, it is important to provide endusers with effective tools to explore information encapsulated in KGs. In this work we present a visual query system that allows users to explore KGs by intuitively constructing tree-shaped conjunctive queries. It is known that systems of this kind suffer from the problem of information overflow: when constructing a query the users have to iteratively choose from a potentially very long list of options, sich as, entities, classes, and data values, where each such choice corresponds to an extension of the query new filters. In order to address this problem we propose an approach to substantially reduce such lists with the help of ranking and by eliminating the so-called deadends, options that yield queries with no answers over a given KG.

Notes

Acknowledgements

This work is partially funded by EU H2020 TheyBuyForYou (780247) project, by the EPSRC projects MaSI\(^3\), DBOnto, ED\(^3\), and by the SIRIUS Centre, Norwegian Research Council project number 237898.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Vidar Klungre
    • 1
    Email author
  • Ahmet Soylu
    • 2
    • 3
  • Martin Giese
    • 1
  • Arild Waaler
    • 1
  • Evgeny Kharlamov
    • 1
    • 4
  1. 1.University of OsloOsloNorway
  2. 2.Norwegian University of Science and TechnologyGøvikNorway
  3. 3.SINTEF DigitalOsloNorway
  4. 4.University of OxfordOxfordUK

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