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Semantic web


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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hal-02984946 , version 1 (01-11-2020)



Jérôme Euzenat, Marie-Christine Rousset. Semantic web. Pierre Marquis, Odile Papini, Henri Prade. A guided tour of artificial intelligence research, Springer, pp.181-207, 2020, 978-3-030-06169-2. ⟨10.1007/978-3-030-06170-8_6⟩. ⟨hal-02984946⟩
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