Abstract

This paper presents an embedding of ontologies expressed in the ALC description logic into a real-valued vector space, comprising restricted existential and universal quantifiers, as well as concept negation and concept disjunction. Our main result states that an ALC ontology is satisfiable in the classical sense iff it is satisfiable by a partial faithful geometric model based on cones. The line of work to which we contribute aims to integrate knowledge representation techniques and machine learning. The new cone-model of ALC proposed in this work gives rise to conic optimization techniques for machine learning, extending previous approaches by its ability to model full ALC.

OriginalspracheEnglisch
Seiten1820 - 1826
Seitenumfang7
DOIs
PublikationsstatusVeröffentlicht - 08.07.2020
Veranstaltung29th International Joint Conference on Artificial Intelligence - Yokohama, Japan
Dauer: 01.01.202101.01.2021
Konferenznummer: 165342

Tagung, Konferenz, Kongress

Tagung, Konferenz, Kongress29th International Joint Conference on Artificial Intelligence
KurztitelIJCAI 2020
Land/GebietJapan
OrtYokohama
Zeitraum01.01.2101.01.21

Strategische Forschungsbereiche und Zentren

  • Zentren: Zentrum für Künstliche Intelligenz Lübeck (ZKIL)
  • Querschnittsbereich: Intelligente Systeme

Fingerprint

Untersuchen Sie die Forschungsthemen von „Cone semantics for logics with negation“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren