On the design of a Natural Logic System for Knowledge Bases

Troels Andreasen*, Henrik Bulskov, Jørgen Fischer Nilsson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Natural logics are logics that take form of stylized natural language sentences within a selected fragment of natural language. Natural Logics are at the same time formal logics with a well-defined syntax and semantics. Therefore, natural logics may be advanced as knowledge 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 implementation principles.
Original languageEnglish
Title of host publicationFoundations of Intelligent Systems : 25th International Symposium, ISMIS 2020, Graz, Austria, September 23–25, 2020, Proceedings
EditorsD. Helic, G. Leitner, M. Stettinger, A. Felfernig, Z.W. Ras
Number of pages8
PublisherSpringer
Publication date2020
Pages 413-421
ISBN (Print)978-3-030-59490-9
ISBN (Electronic)978-3-030-59491-6
DOIs
Publication statusPublished - 2020
Event25th International Symposium on Methodologies for Intelligent Systems: Foundations of Intelligent Systems - Graz University of Technology - ONLINE, Graz, Austria
Duration: 20 May 202022 May 2020
Conference number: 25
https://ismis.ist.tugraz.at/

Symposium

Symposium25th International Symposium on Methodologies for Intelligent Systems
Number25
LocationGraz University of Technology - ONLINE
Country/TerritoryAustria
CityGraz
Period20/05/202022/05/2020
OtherISMIS (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
Internet address
SeriesLecture Notes in Computer Science
Number12117
VolumeLNAI
ISSN0302-9743

Keywords

  • Natural logic
  • Knowledge base systems
  • Deductive Querying
  • Life science applications

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