Abductive Conjunctive Query Answering w.r.t. Ontologies

Ralf Möller; Özgür L. Özcep; Volker Haarslev; Anahita Nafissi; Michael Wessel

doi:10.1007/s13218-015-0399-3

Abductive Conjunctive Query Answering w.r.t. Ontologies

Ralf Möller, Özgür L. Özcep, Volker Haarslev, Anahita Nafissi, Michael Wessel

Institut für Informationssysteme

1 Zitat (Scopus)

Abstract

In this article we investigate abductive conjunctive query answering w.r.t. ontologies and show how use cases can benefit from this kind of query answering service. While practical reasoning systems such as Racer have supported abductive conjunctive query answering for 10 years now, and many projects have exploited this feature, few publications deal with A-box abduction from an implementation perspective. This article gives a generalized overview on features provided by practical systems and also explains optimization techniques needed to meet practical requirements.

Originalsprache	Englisch
Zeitschrift	KI - Künstliche Intelligenz
Jahrgang	30
Ausgabenummer	2
Seiten (von - bis)	177-182
Seitenumfang	6
ISSN	1610-1987
DOIs	https://doi.org/10.1007/s13218-015-0399-3
Publikationsstatus	Veröffentlicht - 13.10.2016

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 3 – Gesundheit und Wohlergehen
SDG 9 – Industrie, Innovation und Infrastruktur

DFG-Fachsystematik

409-06 Informationssysteme, Prozess- und Wissensmanagement
4.43-05 Bild- und Sprachverarbeitung, Computergraphik und Visualisierung, Human Computer Interaction, Ubiquitous und Wearable Computing

Dokumente

10.1007/s13218-015-0399-3

https://www.ifis.uni-luebeck.de/uploads/tx_wapublications/KI-Abductive-QA-2016-Moeller-et-al.pdf

Zitieren

@article{533e162e429c45e79745eccf16e106de,

title = "Abductive Conjunctive Query Answering w.r.t. Ontologies",

abstract = "In this article we investigate abductive conjunctive query answering w.r.t. ontologies and show how use cases can benefit from this kind of query answering service. While practical reasoning systems such as Racer have supported abductive conjunctive query answering for 10 years now, and many projects have exploited this feature, few publications deal with A-box abduction from an implementation perspective. This article gives a generalized overview on features provided by practical systems and also explains optimization techniques needed to meet practical requirements. ",

author = "Ralf M{\"o}ller and {\"O}zcep, \{{\"O}zg{\"u}r L.\} and Volker Haarslev and Anahita Nafissi and Michael Wessel",

year = "2016",

month = oct,

day = "13",

doi = "10.1007/s13218-015-0399-3",

language = "English",

volume = "30",

pages = "177--182",

journal = "KI - K{\"u}nstliche Intelligenz",

issn = "1610-1987",

number = "2",

}

TY - JOUR

T1 - Abductive Conjunctive Query Answering w.r.t. Ontologies

AU - Möller, Ralf

AU - Özcep, Özgür L.

AU - Haarslev, Volker

AU - Nafissi, Anahita

AU - Wessel, Michael

PY - 2016/10/13

Y1 - 2016/10/13

N2 - In this article we investigate abductive conjunctive query answering w.r.t. ontologies and show how use cases can benefit from this kind of query answering service. While practical reasoning systems such as Racer have supported abductive conjunctive query answering for 10 years now, and many projects have exploited this feature, few publications deal with A-box abduction from an implementation perspective. This article gives a generalized overview on features provided by practical systems and also explains optimization techniques needed to meet practical requirements.

AB - In this article we investigate abductive conjunctive query answering w.r.t. ontologies and show how use cases can benefit from this kind of query answering service. While practical reasoning systems such as Racer have supported abductive conjunctive query answering for 10 years now, and many projects have exploited this feature, few publications deal with A-box abduction from an implementation perspective. This article gives a generalized overview on features provided by practical systems and also explains optimization techniques needed to meet practical requirements.

U2 - 10.1007/s13218-015-0399-3

DO - 10.1007/s13218-015-0399-3

M3 - Journal articles

SN - 1610-1987

VL - 30

SP - 177

EP - 182

JO - KI - Künstliche Intelligenz

JF - KI - Künstliche Intelligenz

IS - 2

ER -

Abductive Conjunctive Query Answering w.r.t. Ontologies

Abstract

UN SDGs

DFG-Fachsystematik

Dokumente

Fingerprint

Zitieren