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dc.contributor.authorImhof, Melanie-
dc.contributor.authorBadache, Ismail-
dc.contributor.authorMohand, Boughanem-
dc.date.accessioned2018-07-13T07:07:16Z-
dc.date.available2018-07-13T07:07:16Z-
dc.date.issued2015-
dc.identifier.urihttp://ceur-ws.org/Vol-1391/7-CR.pdfde_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/8025-
dc.description.abstractToday’s information retrieval applications have become increasingly complex. The Social Book Search (SBS) lab at CLEF 2015 allows evaluating retrieval methods on a complex search task with several textual and non-textual meta-data fields. The challenge is to incorporate the different information types (modalities) into a single ranked list. We build a strong textual baseline and combine it with a document prior based on social signals. Further, we include non-textual modalities in relation to the user preferences using random forest learning to rank. Our experiments show that both the social document prior and the learning to rank approach improve the search results.de_CH
dc.language.isoende_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectDatalabde_CH
dc.subject.ddc020: Bibliotheks- und Informationswissenschaftde_CH
dc.titleMultimodal social book searchde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Angewandte Informationstechnologie (InIT)de_CH
zhaw.conference.detailsCLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse, France, 8-11 September 2015de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewNot specifiedde_CH
zhaw.title.proceedingsWorking Notes of CLEF 2015 - Conference and Labs of the Evaluation forumde_CH
zhaw.webfeedInformation Engineeringde_CH
Appears in Collections:Publikationen School of Engineering

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