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Knowledge Engineering

Abstract : Knowledge engineering refers to all technical, scientific and social aspects 1 involved in designing, maintaining and using knowledge-based systems. Research 2 in this domain requires to develop studies on the nature of the knowledge and its 3 representation, either the users' knowledge or the knowledge-based system's knowl-4 edge. It also requires the analysis of what type of knowledge sources is considered, 5 what human-machine interaction is envisaged and more generally the specific end 6 use. To that end, knowledge engineering needs to integrate innovation originating 7 from artificial intelligence, knowledge representation, software engineering as well 8 as modelling. This integration enables both users and software systems to manage and 9 use the knowledge for inference reasoning. Other advances are fuelling new meth-10 ods, software tools and interfaces to support knowledge modelling that are enabled 11 by conceptual or formal knowledge representation languages. This chapter provides 12 an overview of the main issues and major results that are considered as milestones 13 in the domain, with a focus on recent advances marked by the raise of the semantic 14 web, of ontologies and the social web.
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Nathalie Aussenac-Gilles, Jean Charlet, Chantal Reynaud. Knowledge Engineering. Pierre Marquis; Odile Papini; Henri Prade. A Guided Tour of Artificial Intelligence Research, vol. I, 1: Knowledge Representation, Reasoning and Learning, Springer International Publishing, pp.733-768, 2020, 978-3-030-06163-0. ⟨10.1007/978-3-030-06164-7_23⟩. ⟨hal-02857757⟩

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