research-article

A Practical Fine-grained Approach to Resolving Incoherent OWL 2 DL Terminologies

Authors:

Xuefeng FuAuthors Info & Claims

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

Pages 919 - 928

https://doi.org/10.1145/2661829.2662046

Published: 03 November 2014 Publication History

Abstract

Resolving incoherent terminologies is an important task in the maintenance of evolving OWL 2 DL ontologies. Existing approaches to this task are either semi-automatic or based on simple deletion of axioms. There is a need of fine-grained approaches to automatize this task. Since a fine-grained approach should consider multiple choices for modifying an axiom other than the deletion of axioms only, the primary challenges for developing such an approach lie in both the semantics of the repaired results and the efficiency in computing the repaired results. To tackle these challenges, we first introduce the notion of fine-grained repair based on modifying one axiom to zero or more axioms, then propose an efficient incremental method for computing all fine-grained repairs one by one. We also propose a modification function for axioms expressed in OWL 2 DL, which returns weaker axioms. Based on this modification function and the method for computing fine-grained repairs, we develop an automatic approach to resolving incoherent OWL 2 DL terminologies. Our extensive experimental results demonstrate that the proposed approach is efficient and practical.

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Cited By

Baader F(2023)Relating Optimal Repairs in Ontology Engineering with Contraction Operations in Belief ChangeACM SIGAPP Applied Computing Review10.1145/3626307.362630823:3(5-18)Online publication date: 29-Sep-2023
https://dl.acm.org/doi/10.1145/3626307.3626308
Lambrix P(2023)Completing and Debugging Ontologies: State-of-the-art and Challenges in Repairing OntologiesJournal of Data and Information Quality10.1145/359730415:4(1-38)Online publication date: 15-May-2023
https://dl.acm.org/doi/10.1145/3597304
Baader FHong JLanperne MPark JCerny TShahriar H(2023)Optimal Repairs in Ontology Engineering as Pseudo-Contractions in Belief ChangeProceedings of the 38th ACM/SIGAPP Symposium on Applied Computing10.1145/3555776.3577719(983-990)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3555776.3577719
Show More Cited By

Index Terms

A Practical Fine-grained Approach to Resolving Incoherent OWL 2 DL Terminologies
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Nonmonotonic, default reasoning and belief revision
      2. Semantic networks

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cover image ACM Conferences

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

November 2014

2152 pages

ISBN:9781450325981

DOI:10.1145/2661829

General Chairs:
Jianzhong Li
Harbin Inst. of Technology
,
X. Sean Wang
Fudan University
,
Program Chairs:
Minos Garofalakis
Technical University of Crete, Greece
,
Ian Soboroff
National Institute of Standards, USA
,
Torsten Suel
New York University, USA
,
Min Wang
Google Research, USA

Copyright © 2014 ACM.

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Publication History

Published: 03 November 2014

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National Natural Science Foundation of China
Business Intelligence Key Team of Guangdong University of Foreign Studies
Seventh Framework Programme
Guangdong Natural Science Foundation

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CIKM '14

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CIKM '14: 2014 ACM Conference on Information and Knowledge Management

November 3 - 7, 2014

Shanghai, China

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CIKM '14 Paper Acceptance Rate 175 of 838 submissions, 21%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Citations

Cited By

Baader F(2023)Relating Optimal Repairs in Ontology Engineering with Contraction Operations in Belief ChangeACM SIGAPP Applied Computing Review10.1145/3626307.362630823:3(5-18)Online publication date: 29-Sep-2023
https://dl.acm.org/doi/10.1145/3626307.3626308
Lambrix P(2023)Completing and Debugging Ontologies: State-of-the-art and Challenges in Repairing OntologiesJournal of Data and Information Quality10.1145/359730415:4(1-38)Online publication date: 15-May-2023
https://dl.acm.org/doi/10.1145/3597304
Baader FHong JLanperne MPark JCerny TShahriar H(2023)Optimal Repairs in Ontology Engineering as Pseudo-Contractions in Belief ChangeProceedings of the 38th ACM/SIGAPP Symposium on Applied Computing10.1145/3555776.3577719(983-990)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3555776.3577719
Li WJi QZhang SFu XQi G(2023)A graph-based method for interactive mapping revision in DL-LiteExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.118598211:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.118598
Baader FKoopmann PKriegel F(2023)Optimal Repairs in the Description Logic $$\mathcal{E}\mathcal{L}$$ RevisitedLogics in Artificial Intelligence10.1007/978-3-031-43619-2_2(11-34)Online publication date: 24-Sep-2023
https://doi.org/10.1007/978-3-031-43619-2_2
Li YLambrix P(2023)Repairing $$\mathcal{{EL}}$$ Ontologies Using Weakening and CompletingThe Semantic Web10.1007/978-3-031-33455-9_18(298-315)Online publication date: 22-May-2023
https://doi.org/10.1007/978-3-031-33455-9_18
Zhang YWu HGao JZhang YYao RZhu Y(2022)Effective method for detecting error causes from incoherent biological ontologiesMathematical Biosciences and Engineering10.3934/mbe.202234919:7(7388-7409)Online publication date: 2022
https://doi.org/10.3934/mbe.2022349
Ji QQi GYang YLi WHuang SSheng Y(2022)An Embedding-Based Approach to Repairing OWL OntologiesApplied Sciences10.3390/app12241265512:24(12655)Online publication date: 9-Dec-2022
https://doi.org/10.3390/app122412655
Confalonieri RGalliani PKutz OPorello DRighetti GTroquard N(2022)Almost Certain Termination for $$\mathcal {ALC}$$ WeakeningProgress in Artificial Intelligence10.1007/978-3-031-16474-3_54(663-675)Online publication date: 13-Sep-2022
https://doi.org/10.1007/978-3-031-16474-3_54
Zhang YYao ROuyang DGao JLiu F(2021)Debugging incoherent ontology by extracting a clash module and identifying root unsatisfiable conceptsKnowledge-Based Systems10.1016/j.knosys.2021.107043223(107043)Online publication date: Jul-2021
https://doi.org/10.1016/j.knosys.2021.107043
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