research-article

Improving the Competency of First-Order Ontologies

Authors:

German RigauAuthors Info & Claims

K-CAP '15: Proceedings of the 8th International Conference on Knowledge Capture

Article No.: 15, Pages 1 - 8

https://doi.org/10.1145/2815833.2815841

Published: 07 October 2015 Publication History

Abstract

We introduce a new framework to evaluate and improve first-order (FO) ontologies using automated theorem provers (ATPs) on the basis of competency questions (CQs). Our framework includes both the adaptation of a methodology for evaluating ontologies to the framework of first-order logic and a new set of non-trivial CQs designed to evaluate FO versions of SUMO, which significantly extends the very small set of CQs proposed in the literature. Most of these new CQs have been automatically generated from a small set of patterns and the mapping of WordNet to SUMO. Applying our framework, we demonstrate that Adimen-SUMO v2.2 outperforms TPTP-SUMO. In addition, using the feedback provided by ATPs we have set an improved version of Adimen-SUMO (v2.4). This new version outperforms the previous ones in terms of competency. For instance, "Humans can reason" is automatically inferred from Adimen-SUMO v2.4, while it is neither deducible from TPTP-SUMO nor Adimen-SUMO v2.2.

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Cited By

Teja Santosh DBajaj VBajaj V(2018)Development of a Micro Hindi Opinion WordNet and Aligning with Hown Ontology for Automatic Recognition of Opinion Words from Hindi DocumentsSmart and Innovative Trends in Next Generation Computing Technologies10.1007/978-981-10-8657-1_54(697-708)Online publication date: 9-Jun-2018
https://doi.org/10.1007/978-981-10-8657-1_54

Index Terms

Improving the Competency of First-Order Ontologies
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Theory of computation
  1. Logic

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Published In

cover image ACM Other conferences

K-CAP '15: Proceedings of the 8th International Conference on Knowledge Capture

October 2015

209 pages

ISBN:9781450338493

DOI:10.1145/2815833

Conference Chair:
Ken Barker
IBM Watson Research, USA
,
Program Chair:
José Manuel Gómez-Pérez
Expert System, Spain

Copyright © 2015 ACM.

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SIGAI: ACM Special Interest Group on Artificial Intelligence

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New York, NY, United States

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Published: 07 October 2015

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Secretaría de Estado de Investigación, Desarrollo e Innovación
Universidad del País Vasco UPV/EHU

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K-CAP 2015

K-CAP 2015: Knowledge Capture Conference

October 7 - 10, 2015

NY, Palisades, USA

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K-CAP '15 Paper Acceptance Rate 16 of 56 submissions, 29%;

Overall Acceptance Rate 55 of 198 submissions, 28%

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Cited By

Teja Santosh DBajaj VBajaj V(2018)Development of a Micro Hindi Opinion WordNet and Aligning with Hown Ontology for Automatic Recognition of Opinion Words from Hindi DocumentsSmart and Innovative Trends in Next Generation Computing Technologies10.1007/978-981-10-8657-1_54(697-708)Online publication date: 9-Jun-2018
https://doi.org/10.1007/978-981-10-8657-1_54

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