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dc.contributor.authorKelleher, John
dc.contributor.authorKacmajor, Magdalena
dc.date.accessioned2022-03-21T13:13:11Z
dc.date.available2022-03-21T13:13:11Z
dc.date.issued2020
dc.date.submitted2020en
dc.identifier.citationKacmajor, M. and Kelleher, J.D., Capturing and measuring thematic relatedness, Language Resources and Evaluation, 2020, 54, 3, 645-682en
dc.identifier.otherY
dc.description.abstractIn this paper we explain the difference between two aspects of semantic relatedness: taxonomic and thematic relations. We notice the lack of evaluation tools for measuring thematic relatedness, identify two datasets that can be recommended as thematic benchmarks, and verify them experimentally. In further experiments, we use these datasets to perform a comprehensive analysis of the performance of an extensive sample of computational models of semantic relatedness, classified according to the sources of information they exploit. We report models that are best at each of the two dimensions of semantic relatedness and those that achieve a good balance between the two.en
dc.format.extent645-682en
dc.language.isoenen
dc.relation.ispartofseriesLanguage Resources and Evaluation;
dc.relation.ispartofseries54;
dc.relation.ispartofseries3;
dc.rightsYen
dc.subjecttaxonomic relationsen
dc.subjectSemantic relatednessen
dc.subjectThematic relationsen
dc.subjectWord vector representationsen
dc.subjectEvaluation datasetsen
dc.titleCapturing and measuring thematic relatednessen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/kellehjd
dc.identifier.rssinternalid224455
dc.identifier.doihttp://dx.doi.org/10.1007/s10579-019-09452-w
dc.rights.ecaccessrightsopenAccess
dc.contributor.sponsorScience Foundation Ireland (SFI)en
dc.contributor.sponsorGrantNumber13/RC/2106en
dc.identifier.urihttp://hdl.handle.net/2262/98327


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