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  2. School of Engineering
  3. Publikationen
  4. Publikationen School of Engineering
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dc.contributor.authorTaranova, Anastasia-
dc.contributor.authorBraschler, Martin-
dc.date.accessioned2022-03-02T14:05:23Z-
dc.date.available2022-03-02T14:05:23Z-
dc.date.issued2021-
dc.identifier.isbn978-3-030-72239-5de_CH
dc.identifier.isbn978-3-030-72240-1de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/24429-
dc.description.abstractWe study the textual complexity of documents as an aspect of the Information Retrieval process that influences retrieval effectiveness. Our experiments show that in many cases user queries allow determining which linguistic competency level best suits an underlying information need. The paper investigates promising first approaches on how to do so automatically and compares them to an idealistic baseline. By filtering out documents of unexpected textual complexity, we find improved search results mainly when using precision-oriented effectiveness measures.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.subjectTextual complexityde_CH
dc.subjectDocument relevancede_CH
dc.subject.ddc020: Bibliotheks- und Informationswissenschaftde_CH
dc.titleTextual complexity as an indicator of document relevancede_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-030-72240-1_42de_CH
zhaw.conference.details43rd European Conference on Information Retrieval, Lucca (online), 28 March - 1 April 2021de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end417de_CH
zhaw.pages.start410de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number12657de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsAdvances in Information Retrievalde_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedInformation Engineeringde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Taranova, A., & Braschler, M. (2021). Textual complexity as an indicator of document relevance [Conference paper]. Advances in Information Retrieval, 410–417. https://doi.org/10.1007/978-3-030-72240-1_42
Taranova, A. and Braschler, M. (2021) ‘Textual complexity as an indicator of document relevance’, in Advances in Information Retrieval. Cham: Springer, pp. 410–417. Available at: https://doi.org/10.1007/978-3-030-72240-1_42.
A. Taranova and M. Braschler, “Textual complexity as an indicator of document relevance,” in Advances in Information Retrieval, 2021, pp. 410–417. doi: 10.1007/978-3-030-72240-1_42.
TARANOVA, Anastasia und Martin BRASCHLER, 2021. Textual complexity as an indicator of document relevance. In: Advances in Information Retrieval. Conference paper. Cham: Springer. 2021. S. 410–417. ISBN 978-3-030-72239-5
Taranova, Anastasia, and Martin Braschler. 2021. “Textual Complexity as an Indicator of Document Relevance.” Conference paper. In Advances in Information Retrieval, 410–17. Cham: Springer. https://doi.org/10.1007/978-3-030-72240-1_42.
Taranova, Anastasia, and Martin Braschler. “Textual Complexity as an Indicator of Document Relevance.” Advances in Information Retrieval, Springer, 2021, pp. 410–17, https://doi.org/10.1007/978-3-030-72240-1_42.


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