Article

Learning domain ontologies for Web service descriptions: an experiment in bioinformatics

Authors:

Gilad MishneAuthors Info & Claims

WWW '05: Proceedings of the 14th international conference on World Wide Web

Pages 190 - 198

https://doi.org/10.1145/1060745.1060776

Published: 10 May 2005 Publication History

Abstract

The reasoning tasks that can be performed with semantic web service descriptions depend on the quality of the domain ontologies used to create these descriptions. However, building such domain ontologies is a time consuming and difficult task.We describe an automatic extraction method that learns domain ontologies for web service descriptions from textual documentations attached to web services. We conducted our experiments in the field of bioinformatics by learning an ontology from the documentation of the web services used in ^myGrid, a project that supports biology experiments on the Grid. Based on the evaluation of the extracted ontology in the context of the project, we conclude that the proposed extraction method is a helpful tool to support the process of building domain ontologies for web service descriptions.

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Cited By

Al-Aswadi FChan HGan K(2019)Automatic ontology construction from text: a review from shallow to deep learning trendArtificial Intelligence Review10.1007/s10462-019-09782-9Online publication date: 8-Nov-2019
https://doi.org/10.1007/s10462-019-09782-9
Wei XZeng DLuo X(2018)Concept evolution analysis based on the Dissipative Structure of Concept Semantic SpaceFuture Generation Computer Systems10.1016/j.future.2017.10.04281:C(384-394)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1016/j.future.2017.10.042
Ruangrajitpakorn TKongkachandra RSongmuang PSupnithi T(2018)Automatic Ontology Development from Semi-structured Data in Web-Portal: Towards Ontology of Thai Rice KnowledgeSemantic Technology10.1007/978-3-030-04284-4_18(262-276)Online publication date: 14-Nov-2018
https://doi.org/10.1007/978-3-030-04284-4_18
Show More Cited By

Index Terms

Learning domain ontologies for Web service descriptions: an experiment in bioinformatics
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
  2. Machine learning
    1. Learning settings
2. Information systems
  1. Information systems applications
  2. World Wide Web
    1. Web applications
    2. Web services

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cover image ACM Conferences

WWW '05: Proceedings of the 14th international conference on World Wide Web

May 2005

781 pages

ISBN:1595930469

DOI:10.1145/1060745

Conference Chairs:
Allan Ellis
Southern Cross University
,
Tatsuya Hagino
Keio University

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 10 May 2005

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Cited By

Al-Aswadi FChan HGan K(2019)Automatic ontology construction from text: a review from shallow to deep learning trendArtificial Intelligence Review10.1007/s10462-019-09782-9Online publication date: 8-Nov-2019
https://doi.org/10.1007/s10462-019-09782-9
Wei XZeng DLuo X(2018)Concept evolution analysis based on the Dissipative Structure of Concept Semantic SpaceFuture Generation Computer Systems10.1016/j.future.2017.10.04281:C(384-394)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1016/j.future.2017.10.042
Ruangrajitpakorn TKongkachandra RSongmuang PSupnithi T(2018)Automatic Ontology Development from Semi-structured Data in Web-Portal: Towards Ontology of Thai Rice KnowledgeSemantic Technology10.1007/978-3-030-04284-4_18(262-276)Online publication date: 14-Nov-2018
https://doi.org/10.1007/978-3-030-04284-4_18
(2017)Building business process ontology based on concept hierarchy modelInternational Journal of Computational Science and Engineering10.5555/3141013.314102115:1-2(66-73)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.5555/3141013.3141021
(2017)Building business process ontology based on concept hierarchy modelInternational Journal of Computational Science and Engineering10.5555/3140984.314099215:1-2(66-73)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.5555/3140984.3140992
Fanjiang YSyu YMa SKuo J(2017)An Overview and Classification of Service Description Approaches in Automated Service Composition ResearchIEEE Transactions on Services Computing10.1109/TSC.2015.246153810:2(176-189)Online publication date: 1-Mar-2017
https://doi.org/10.1109/TSC.2015.2461538
El Idrissi Esserhrouchni OFrikh BOuhbi BIbrahim I(2017)Learning domain taxonomies: the TaxoLine approachInternational Journal of Web Information Systems10.1108/IJWIS-04-2017-002413:3(281-301)Online publication date: 21-Aug-2017
https://doi.org/10.1108/IJWIS-04-2017-0024
He ZChen ZOh SHou JBian J(2017)Enriching consumer health vocabulary through mining a social Q&A siteJournal of Biomedical Informatics10.1016/j.jbi.2017.03.01669:C(75-85)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.jbi.2017.03.016
Maabed UEl-Fatatry AEl-Zoghabi A(2016)Enhancing Interface Understandability as a Means for Better Discovery of Web ServicesInternational Journal of Information Technology and Web Engineering10.4018/IJITWE.201610010111:4(1-23)Online publication date: 1-Oct-2016
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Khemaja M(2016)Domain driven design and provision of micro-services to build emerging learning systemsProceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality10.1145/3012430.3012643(1035-1042)Online publication date: 2-Nov-2016
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