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dc.contributor.authorArcan, Mihael
dc.contributor.authorTurchi, Marco
dc.contributor.authorBuitelaar, Paul
dc.date.accessioned2019-01-31T14:45:53Z
dc.date.available2019-01-31T14:45:53Z
dc.date.issued2015-07-26
dc.identifier.citationArcan, Mihael, Turchi, Marco, & Buitelaar, Paul. (2015). Knowledge portability with semantic expansion of ontology labels. Paper presented at the 53rd Annual Meeting of the Association for Computational Linguistics and 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL-IJCNLP 2015), Beijing, China, 26-31 Julyen_IE
dc.identifier.urihttp://hdl.handle.net/10379/14895
dc.description.abstractOur research focuses on the multilingual enhancement of ontologies that, often represented only in English, need to be translated in different languages to enable knowledge access across languages. Ontology translation is a rather different task then the classic document translation, because ontologies contain highly specific vocabulary and they lack contextual information. For these reasons, to improve automatic ontology translations, we first focus on identifying relevant unambiguous and domain-specific sentences from a large set of generic parallel corpora. Then, we leverage Linked Open Data resources, such as DBPedia, to isolate ontologyspecific bilingual lexical knowledge. In both cases, we take advantage of the semantic information of the labels to select relevant bilingual data with the aim of building an ontology-specific statistical machine translation system. We evaluate our approach on the translation of a medical ontology, translating from English into German. Our experiment shows a significant improvement of around 3 BLEU points compared to a generic as well as a domain-specific translation approach.en_IE
dc.description.sponsorshipThis publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight) and the European Union supported projects LIDER (ICT-2013.4.1-610782) and MixedEmotions (H2020-644632).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherAssociation for Computational Linguisticsen_IE
dc.relation.ispartofAssociation for Computational Linguistics (ACL-2015)en
dc.subjectKnowledge portabilityen_IE
dc.subjectSemantic expansionen_IE
dc.subjectOntology labelsen_IE
dc.titleKnowledge portability with semantic expansion of ontology labelsen_IE
dc.typeConference Paperen_IE
dc.date.updated2019-01-23T17:52:02Z
dc.local.publishedsourcehttp://www.aclweb.org/anthology/P/P15/P15-1069.pdfen_IE
dc.description.peer-reviewednon-peer-reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderHorizon 2020en_IE
dc.internal.rssid13192032
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/FP7::SP1::ICT/610782/EU/LIDER: Linked Data as an enabler of cross-media and multilingual content analytics for enterprises across Europe/LIDERen_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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