research-article

Fuzzy semantic web ontology learning from fuzzy UML model

Authors:

Xiangfu MengAuthors Info & Claims

CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management

Pages 1007 - 1016

https://doi.org/10.1145/1645953.1646082

Published: 02 November 2009 Publication History

Abstract

How to quickly and cheaply construct Web ontologies has become a key technology to enable the Semantic Web. Classical ontologies are not sufficient for handling imprecise and uncertain information that is commonly found in many application domains. In this paper, we propose an approach for constructing fuzzy ontologies from fuzzy UML models, in which the fuzzy ontology consists of fuzzy ontology structure and instances. Firstly, the fuzzy UML model is investigated in detail, and a kind of formal definition of fuzzy UML models is proposed. Then, a kind of fuzzy ontology called fuzzy OWL DL ontology is introduced. Furthermore, we consider the fuzzy UML model and the corresponding fuzzy UML instantiations (i.e., object diagrams) simultaneously, and translate them into the fuzzy ontology structure and the fuzzy ontology instances, respectively. In addition, since a fuzzy OWL DL ontology is equivalent to a fuzzy Description Logic f-SHOIN(D) knowledge base, how the reasoning problems of fuzzy UML models (e.g., consistency, subsumption, equivalence, and redundancy) may be reasoned through reasoning mechanism of f-SHOIN(D) is investigated, which can help to construct fuzzy ontologies more exactly.

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Cited By

Zhang FMa Z(2013)Construction of Fuzzy Ontologies from Fuzzy UML ModelsInternational Journal of Computational Intelligence Systems10.1080/18756891.2013.7807356:3(442-472)Online publication date: May-2013
https://doi.org/10.1080/18756891.2013.780735
Zhang FMa ZYan L(2013)Construction of fuzzy ontologies from fuzzy XML modelsKnowledge-Based Systems10.1016/j.knosys.2012.12.01542(20-39)Online publication date: 1-Apr-2013
https://dl.acm.org/doi/10.1016/j.knosys.2012.12.015
Zhang FMa ZYan LCheng J(2013)Construction of fuzzy OWL ontologies from fuzzy EER models: A semantics-preserving approachFuzzy Sets and Systems10.1016/j.fss.2013.03.016229(1-32)Online publication date: Oct-2013
https://doi.org/10.1016/j.fss.2013.03.016
Show More Cited By

Index Terms

Fuzzy semantic web ontology learning from fuzzy UML model
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
  2. Machine learning
    1. Learning settings

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cover image ACM Conferences

CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management

November 2009

2162 pages

ISBN:9781605585123

DOI:10.1145/1645953

General Chairs:
David Cheung
University of Hong Kong, Hong Kong
,
Il-Yeol Song
Drexel University, USA
,
Program Chairs:
Wesley Chu
UCLA, USA
,
Xiaohua Hu
Drexel University, USA
,
Jimmy Lin
University of Maryland, USA

Copyright © 2009 ACM.

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Published: 02 November 2009

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November 2 - 6, 2009

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Cited By

Zhang FMa Z(2013)Construction of Fuzzy Ontologies from Fuzzy UML ModelsInternational Journal of Computational Intelligence Systems10.1080/18756891.2013.7807356:3(442-472)Online publication date: May-2013
https://doi.org/10.1080/18756891.2013.780735
Zhang FMa ZYan L(2013)Construction of fuzzy ontologies from fuzzy XML modelsKnowledge-Based Systems10.1016/j.knosys.2012.12.01542(20-39)Online publication date: 1-Apr-2013
https://dl.acm.org/doi/10.1016/j.knosys.2012.12.015
Zhang FMa ZYan LCheng J(2013)Construction of fuzzy OWL ontologies from fuzzy EER models: A semantics-preserving approachFuzzy Sets and Systems10.1016/j.fss.2013.03.016229(1-32)Online publication date: Oct-2013
https://doi.org/10.1016/j.fss.2013.03.016
Bhattacharya IGhosh S(2013)Formal Representation of Fuzzy Data Model Using Description LogicComputational Science and Its Applications – ICCSA 201310.1007/978-3-642-39649-6_8(108-119)Online publication date: 2013
https://doi.org/10.1007/978-3-642-39649-6_8
Ma ZZhang FYan LCheng JMa ZZhang FYan LCheng J(2013)Fuzzy Description Logic and Ontology Extraction from Fuzzy Data ModelsFuzzy Knowledge Management for the Semantic Web10.1007/978-3-642-39283-2_5(99-156)Online publication date: 26-Sep-2013
https://doi.org/10.1007/978-3-642-39283-2_5
Ma ZZhang FYan LCheng JMa ZZhang FYan LCheng J(2013)Fuzzy Description Logics and Fuzzy OntologiesFuzzy Knowledge Management for the Semantic Web10.1007/978-3-642-39283-2_4(61-97)Online publication date: 26-Sep-2013
https://doi.org/10.1007/978-3-642-39283-2_4
Lin CHong T(2013)A survey of fuzzy web miningWIREs Data Mining and Knowledge Discovery10.1002/widm.10913:3(190-199)Online publication date: 18-Apr-2013
https://doi.org/10.1002/widm.1091
Liu CQi GWang HYu Y(2012)Reasoning with Large Scale Ontologies in Fuzzy pD* Using MapReduceIEEE Computational Intelligence Magazine10.1109/MCI.2012.21885897:2(54-66)Online publication date: 1-May-2012
https://dl.acm.org/doi/10.1109/MCI.2012.2188589
Lingyu Zhang Ma Z(2012)ICFC: A method for computing semantic similarity among fuzzy concepts in a fuzzy ontology2012 IEEE International Conference on Fuzzy Systems10.1109/FUZZ-IEEE.2012.6251166(1-8)Online publication date: Jun-2012
https://doi.org/10.1109/FUZZ-IEEE.2012.6251166
Alexopoulos PWallace MKafentzis KAskounis D(2012)IKARUS-Onto: a methodology to develop fuzzy ontologies from crisp onesKnowledge and Information Systems10.1007/s10115-011-0457-632:3(667-695)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s10115-011-0457-6
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