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Semantic Web

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A Guided Tour of Artificial Intelligence Research

Abstract

The semantic web aims at making web content interpretable. It is no less than offering knowledge representation at web scale. The main ingredients used in this context are the representation of assertional knowledge through graphs, the definition of the vocabularies used in graphs through ontologies, and the connection of these representations through the web. Artificial intelligence techniques and, more specifically, knowledge representation techniques, are put to use and to the test by the semantic web. Indeed, they have to face typical problems of the web: scale, heterogeneity, incompleteness, and dynamics. This chapter provides a short presentation of the state of the semantic web and refers to other chapters concerning those techniques at work in the semantic web.

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Notes

  1. 1.

    WorldWide Web Consortium: the organisation in charge of recommending web technologies.

  2. 2.

    Sources: http://stats.lod2.eu/ and http://lov.okfn.org.

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Author information

Authors and Affiliations

  1. Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, 38000, Grenoble, France

    Jérôme Euzenat

  2. Université Grenoble Alpes and Institut Universitaire de France, CNRS, Inria, Grenoble INP, LIG, 38000, Grenoble, France

    Marie-Christine Rousset

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  1. Jérôme Euzenat
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Correspondence to Jérôme Euzenat .

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  1. CRIL-CNRS, Université d'Artois and Institut Universitaire de France, Lens, France

    Pierre Marquis

  2. Aix Marseille Université, Université de Toulon, CNRS, LIS, Marseille, France

    Odile Papini

  3. IRIT, CNRS and Université Paul Sabatier, Toulouse, France

    Henri Prade

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Euzenat, J., Rousset, MC. (2020). Semantic Web. In: Marquis, P., Papini, O., Prade, H. (eds) A Guided Tour of Artificial Intelligence Research. Springer, Cham. https://doi.org/10.1007/978-3-030-06170-8_6

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