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Annual International Symposium on Information Management and Big Data

SIMBig 2018: Information Management and Big Data pp 7–12Cite as

Which Is the Tallest Building in Europe? Representing and Reasoning About Knowledge

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 898))

Abstract

The need for representing knowledge is ubiquitous in applications; for example, Google needs to represent knowledge about the location and height of building in order to answer questions such as “which is the tallest building in Europe”. Google uses a graph to represent such knowledge, and so-called knowledge graphs are becoming increasingly popular as a knowledge representation formalism. Adding some form of rules greatly increases the power and utility of knowledge graphs, but can also lead to theoretical and/or practical tractability problems. In this papers we will briefly survey the relevant issues and possible solutions, and show that rule enhanced knowledge graphs are extremely powerful, can be given a formal logic-based semantics, and are highly scalable in practice.

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Notes

  1. 1.

    wikipedia.org/wiki/Knowledge_Graph.

  2. 2.

    wikipedia.org/wiki/Eiffel_Tower.

  3. 3.

    Recall the use of the term “predicate” in RDF triples.

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Author information

Authors and Affiliations

  1. University of Oxford, Oxford, UK

    Ian Horrocks

Authors
  1. Ian Horrocks
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Correspondence to Ian Horrocks .

Editor information

Editors and Affiliations

  1. Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA

    Juan Antonio Lossio-Ventura

  2. Fondazione Bruno Kessler, Trento, Italy

    Denisse Muñante

  3. Facultad de Ingeniería, University of the Pacific, Jesús María, Lima, Peru

    Hugo Alatrista-Salas

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Horrocks, I. (2019). Which Is the Tallest Building in Europe? Representing and Reasoning About Knowledge. In: Lossio-Ventura, J., Muñante, D., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2018. Communications in Computer and Information Science, vol 898. Springer, Cham. https://doi.org/10.1007/978-3-030-11680-4_2

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  • DOI: https://doi.org/10.1007/978-3-030-11680-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11679-8

  • Online ISBN: 978-3-030-11680-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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