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Towards Knowledge Graphs Validation Through Weighted Knowledge Sources

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Knowledge Graphs and Semantic Web (KGSWC 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1459))

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Abstract

The performance of applications, such as personal assistants and search engines, relies on high-quality knowledge bases, a.k.a. Knowledge Graphs (KGs). To ensure their quality one important task is knowledge validation, which measures the degree to which statements or triples of KGs are semantically correct. KGs inevitably contain incorrect and incomplete statements, which may hinder their adoption in business applications as they are not trustworthy. In this paper, we propose and implement a Validator that computes a confidence score for every triple and instance in KGs. The computed score is based on finding the same instances across different weighted knowledge sources and comparing their features. We evaluate our approach by comparing its results against a baseline validation. Our results suggest that we can validate KGs with an f-measure of at least 75%. Time-wise, the Validator, performed a validation of 2530 instances in 15 min approximately. Furthermore, we give insights and directions toward a better architecture to tackle KG validation.

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Notes

  1. 1.

    https://schema.org/.

  2. 2.

    https://github.com/DeFacto/DeFacto.

  3. 3.

    https://github.com/dice-group/Leopard.

  4. 4.

    https://github.com/dice-group/FactCheck.

  5. 5.

    http://qweb.cs.aau.dk/factify/.

  6. 6.

    https://github.com/sheffieldnlp/fever-naacl-2018.

  7. 7.

    https://github.com/DeFacto/FactBench.

  8. 8.

    https://www.w3.org/TR/turtle/.

  9. 9.

    Domain Specification are design patterns for annotating data based on Schema.org. This process implies to remove types and properties from Schema.org, or add types and properties defined in an external extension of Schema.org.

  10. 10.

    Schema alignment is the task of determining the correspondences between various schemas.

  11. 11.

    To define weights, a proper quality analysis of the knowledge sources must be carried out [8]. It may assist users in defining degrees of importance for each knowledge source.

  12. 12.

    The default threshold is defined to 0.5.

  13. 13.

    https://github.com/AmarTauqeer/graph-validation.

  14. 14.

    https://developer.mozilla.org/en-US/docs/Web/JavaScript.

  15. 15.

    https://getbootstrap.com/.

  16. 16.

    https://graphdb.sti2.at/sparql.

  17. 17.

    https://github.com/AmarTauqeer/graph-validation/tree/master/data.

  18. 18.

    https://developers.google.com/maps/documentation/places/.

  19. 19.

    https://www.openstreetmap.org/.

  20. 20.

    https://yandex.com/dev/maps/.

  21. 21.

    https://tarql.github.io/.

  22. 22.

    https://dbpedia.org/page/Juan_Carlos_I.

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Acknowledgments

This work has been partially funded by the project WordLiftNG within the Eureka, Eurostars Programme of the European Union (grant agreement number 877857 with the Austrian Research Promotion Agency (FFG)) and the industrial research project MindLab (https://mindlab.ai/). We would like to thank Prof. Dr. Dieter Fensel for his insightful comments regarding the definition of the overall validation approach.

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Authors and Affiliations

  1. Semantic Technology Institute (STI) Innsbruck, Department of Computer Science, University of Innsbruck, Innsbruck, Austria

    Elwin Huaman, Amar Tauqeer & Anna Fensel

  2. Wageningen Data Competence Center and Consumption and Healthy Lifestyles Chair Group, Wageningen University & Research, Wageningen, The Netherlands

    Anna Fensel

Authors
  1. Elwin Huaman
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  2. Amar Tauqeer
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  3. Anna Fensel
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Corresponding author

Correspondence to Elwin Huaman .

Editor information

Editors and Affiliations

  1. Tinamica/Universidad Internacional de la Rioja, Madrid, Madrid, Spain

    Boris Villazón-Terrazas

  2. Tamaulipas Autonomous University, Ciudad Victoria, Mexico

    Fernando Ortiz-Rodríguez

  3. Tamaulipas Autonomous University, Ciudad Victoria, Mexico

    Sanju Tiwari

  4. Texas A&M University – Kingsville, Kingsville, TX, USA

    Ayush Goyal

  5. Vardhaman College of Engineering, Hyderabad, Telangana, India

    MA Jabbar

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Huaman, E., Tauqeer, A., Fensel, A. (2021). Towards Knowledge Graphs Validation Through Weighted Knowledge Sources. In: Villazón-Terrazas, B., Ortiz-Rodríguez, F., Tiwari, S., Goyal, A., Jabbar, M. (eds) Knowledge Graphs and Semantic Web. KGSWC 2021. Communications in Computer and Information Science, vol 1459. Springer, Cham. https://doi.org/10.1007/978-3-030-91305-2_4

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  • DOI: https://doi.org/10.1007/978-3-030-91305-2_4

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