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dc.contributor.authorMyklebust, Erik Bryhn
dc.contributor.authorJimenez-Ruiz, Ernesto
dc.contributor.authorChen, Jiaoyan
dc.contributor.authorWolf, Raoul
dc.contributor.authorTollefsen, Knut-Erik
dc.date.accessioned2020-01-24T12:28:00Z
dc.date.available2020-01-24T12:28:00Z
dc.date.created2019-12-29T14:43:13Z
dc.date.issued2019
dc.identifier.citationCEUR Workshop Proceedings. 2019, 2456, 37-40.nb_NO
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/11250/2637838
dc.description.abstractExploring the effects of a chemical compound on a species takes a considerable experimental effort. Appropriate methods for estimating and suggesting new effects can dramatically reduce the work needed to be done by a laboratory. Here, we explore the suitability of using a knowledge graph embedding approach for ecotoxicological effect prediction. A knowledge graph has been constructed from publicly available data sets, including a species taxonomy and chemical knowledge. These knowledge sources are integrated by ontology alignment techniques. Our experimental results show that the knowledge graph and its embeddings augment the baseline models.nb_NO
dc.language.isoengnb_NO
dc.publisherCEUR Workshop Proceedingsnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleKnowledge graph embedding for ecotoxicological effect predictionnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.rights.holderCopyright 2019 for this paper by its authorsnb_NO
dc.source.pagenumber37-40nb_NO
dc.source.volume2456nb_NO
dc.source.journalCEUR Workshop Proceedingsnb_NO
dc.identifier.cristin1764184
dc.relation.projectNorges forskningsråd: 272414nb_NO
dc.relation.projectNorges forskningsråd: 268294nb_NO
cristin.unitcode7464,20,18,0
cristin.unitcode7464,20,13,0
cristin.unitnameMiljøinformatikk
cristin.unitnameØkotoksikologi
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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