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dc.contributor.authorSmith, Ellery-
dc.contributor.authorWeiler, Andreas-
dc.contributor.authorBraschler, Martin-
dc.date.accessioned2022-03-16T11:06:17Z-
dc.date.available2022-03-16T11:06:17Z-
dc.date.issued2021-
dc.identifier.isbn978-3-030-85250-4de_CH
dc.identifier.isbn978-3-030-85251-1de_CH
dc.identifier.issn0302-9743de_CH
dc.identifier.issn1611-3349de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/24567-
dc.description.abstractWe discuss a domain-specific retrieval application for matching job seekers with open positions that uses a novel syntactic method of extracting skill-terms from the text of natural language job advertisements. Our new method is contrasted with two word embeddings methods, using word2vec. We define the notion of a skill headword, and present an algorithm that learns syntactic dependency patterns to recognize skill-terms. In all metrics, our syntactic method outperforms both word embeddings methods. Moreover, the word embeddings approaches were unable to model a meaningful distinction between skill-terms and non-skill-terms, while our syntactic approach was able to perform this successfully. We also show how these extracted skills can be used to automatically construct a semantic job-skills ontology, and facilitate a job-to-candidate matching system.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofseriesLecture Notes in Computer Sciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectInformation retrievalde_CH
dc.subjectDomain-specific retrievalde_CH
dc.subjectTerm extractionde_CH
dc.subjectNatural language processingde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleSkill extraction for domain-specific text retrieval in a job-matching platformde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Angewandte Informationstechnologie (InIT)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-030-85251-1_10de_CH
zhaw.conference.details12th International Conference of the CLEF Association (CLEF 2021), virtual event, 21–24 September 2021de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end128de_CH
zhaw.pages.start116de_CH
zhaw.parentwork.editorCandan, K. Selçuk-
zhaw.parentwork.editorIonescu, Bogdan-
zhaw.parentwork.editorGoeuriot, Lorraine-
zhaw.parentwork.editorLarsen, Birger-
zhaw.parentwork.editorMüller, Henning-
zhaw.parentwork.editorJoly, Alexis-
zhaw.parentwork.editorMaistro, Maria-
zhaw.parentwork.editorPiroi, Florina-
zhaw.parentwork.editorFaggioli, Gugliemlo-
zhaw.parentwork.editorFerro, Nicola-
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number12880de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsExperimental IR Meets Multilinguality, Multimodality, and Interactionde_CH
zhaw.webfeedInformation Engineeringde_CH
zhaw.funding.zhawSkillue - Digitaler Marktplatz für Fähigkeiten und Marktwertede_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Engineering

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