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dc.contributor.authorArcan, Mihael
dc.contributor.authorDragoni, Mauro
dc.contributor.authorBuitelaar, Paul
dc.date.accessioned2019-01-29T15:54:23Z
dc.date.available2019-01-29T15:54:23Z
dc.date.issued2016
dc.identifier.citationArcan M., Dragoni M., Buitelaar P. (2016) ESSOT: An Expert Supporting System for Ontology Translation. In: Métais E., Meziane F., Saraee M., Sugumaran V., Vadera S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science, vol 9612. Springer, Chamen_IE
dc.identifier.isbn978-3-319-41754-7
dc.identifier.urihttp://hdl.handle.net/10379/14884
dc.description.abstractTo enable knowledge access across languages, ontologies, mostly represented only in English, need to be translated into different languages. The main challenge in translating ontologies with machine translation is to disambiguate an ontology label with respect to the domain modelled by the ontology itself; however, a crucial requirement is to have translations validated by experts before the ontologies are deployed. Real-world applications have to implement a support system addressing this task to help experts in validating automatically generated translations. In this paper, we present ESSOT, an Expert Supporting System for Ontology Translation. The peculiarity of this system is to exploit the semantic information of the label’s context to improve the quality of label translations. The system has been tested within the Organic.Lingua project by translating the modelled ontology in three languages, whereby the results are compared with translations provided by the Microsoft Translator API. The provided results demonstrate the viability of our proposed approach.en_IE
dc.description.sponsorshipThis publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 and the European Unions Horizon 2020 programme MixedEmotions (Grant Number 644632).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherSpringer Verlagen_IE
dc.relation.ispartofInternational Conference on Applications of Natural Language to Information Systemsen
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/ie/
dc.subjectMachine Translationen_IE
dc.subjectStatistical Machine Translationen_IE
dc.subjectTranslation Serviceen_IE
dc.subjectParallel Corpusen_IE
dc.titleESSOT: an expert supporting system for ontology translationen_IE
dc.typeConference Paperen_IE
dc.date.updated2019-01-23T17:47:24Z
dc.identifier.doi10.1007/978-3-319-41754-7_6
dc.local.publishedsourcehttps://doi.org/10.1007/978-3-319-41754-7_6en_IE
dc.description.peer-reviewednon-peer-reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderHorizon 2020en_IE
dc.internal.rssid13192043
dc.local.contactMihael Arcan. Email: mihael.arcan@insight-centre.org
dc.local.copyrightcheckedYes
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE
dcterms.projectinfo:eu-repo/grantAgreement/EC/H2020::IA/644632/EU/Social Semantic Emotion Analysis for Innovative Multilingual Big Data Analytics Markets/MixedEmotionsen_IE
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