On the design of a Natural Logic System for Knowledge Bases

Troels Andreasen*, Henrik Bulskov, Jørgen Fischer Nilsson

*Corresponding author

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

Abstract

Natural logics are logics that take form of stylized natural language sentences within a selected fragment of natural language. Nat- ural Logics are at the same time formal logics with a well-defined syn- tax and semantics. Therefore, natural logics may be advanced as knowl- edge base logics enhancing explainability of query answers. This paper is concerned with a natural logic, NaturaLog, having been proposed as a deductive knowledge base language. The paper briefly reviews and brings together in compact form the main points in our previously but separately published design proposals, systems functionalities and im- plementation principles.
OriginalsprogEngelsk
TitelFoundations of Intelligent Systems - 25th International Symposium, ISMIS 2020, Proceedings : 25th International Symposium, ISMIS 2020, Graz, Austria, September 23–25, 2020, Proceedings
RedaktørerDenis Helic, Martin Stettinger, Alexander Felfernig, Gerhard Leitner, Zbigniew W. Ras
Antal sider8
ForlagSpringer
Publikationsdato2020
Sider 413-421
ISBN (Trykt)978-3-030-59490-9
ISBN (Elektronisk)978-3-030-59491-6
DOI
StatusUdgivet - 2020
Begivenhed25th International Symposium on Methodologies for Intelligent Systems: Foundations of Intelligent Systems - Graz University of Technology - ONLINE, Graz, Østrig
Varighed: 20 maj 202022 maj 2020
Konferencens nummer: 25
https://ismis.ist.tugraz.at/

Symposium

Symposium25th International Symposium on Methodologies for Intelligent Systems
Nummer25
LokationGraz University of Technology - ONLINE
Land/OmrådeØstrig
ByGraz
Periode20/05/202022/05/2020
AndetISMIS (this year, it is organized as an online event) is an established and prestigious conference for exchanging the latest research results in building intelligent systems. It provides a basis for exchanging research results and transport scientific achievements towards industrial applications. The scope of ISMIS is to present a wide range of topics related to the application of Artificial Intelligence techniques related to areas such as decision support, knowledge representation, logical programming, knowledge-based systems, machine learning, planning, computer vision, information retrieval, configuration and diagnosis. The conference also focus on interdisciplinary research in AI-related fields, for example, decision support systems and human decision making or recommender systems and human personality, and knowledge-based systems development and cognitive aspects of knowledge understanding.Conference ScopeMotivated by recent developments in sub-symbolic AI and the continuous emergence of new application domains, this year’s conference theme is “Towards explainable Artificial Intelligence”. We this focus, ISMI2020 contributes to emerging challenges related to the explainability of system outputs which experience an increased relevance in areas such as autonomous driving, intelligent sales assistants, and different further application domains such as medicine, intelligent maintenance, and eLearning.ISMIS 2020 is intended to attract individuals who are actively engaged both in theoretical and practical aspects of intelligent systems. The goal is to provide a platform for a useful exchange between theoreticians and practitioners, and to foster the cross-fertilization of ideas: Relevant conference topics include but are not limited to:Explainable AI (XAI)Machine LearningDeep learningData MiningRecommender SystemsConstraint based systemsAutonomous systemsApplications (Configuration, Internet of Things, Financial Services, e-Health…)Intelligent user interfacesUser ModelingHuman computationSocially-aware systemsAutonomous systemsDigital librariesIntelligent AgentsInformation RetrievalNatural Language ProcessingKnowledge IntegrationKnowledge VisualizationKnowledge RepresentationSoft ComputingWeb & Text Mining
Internetadresse
NavnLecture Notes in Computer Science
Nummer12117
Vol/bindLNAI
ISSN0302-9743

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