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dc.contributor.authorPreminger, Michael
dc.contributor.authorFludal, Gjertrud
dc.date.accessioned2016-11-08T08:15:46Z
dc.date.accessioned2017-03-16T10:02:05Z
dc.date.available2016-11-08T08:15:46Z
dc.date.available2017-03-16T10:02:05Z
dc.date.issued2016
dc.identifier.citationCEUR Workshop Proceedings 2016, 1609:1145-1154language
dc.identifier.issn1613-0073
dc.identifier.urihttps://hdl.handle.net/10642/4291
dc.description.abstractIn this article we describe the OAUC’s participation in the CLEF 2016 SBS Search Suggestion track. We are trying to represent appeal elements, used in readers’ advisory theory and practice, to see if they can be used in an automatic retrieval and recommendation context. We are still working with the pace appeal element, used in fiction to capture how quickly the buildup of the story or the plot is. New this year is the use of intellectually coded appeal-element data done by EBSCO as part of the NoveList R © service (our gratitude to EBSCO for providing the data).language
dc.language.isoenlanguage
dc.publisherCEUR Workshop Proceedingslanguage
dc.titleOAUC at CLEF2016 SBS Lab: Using Appeal Elements to Improve Automatic Book Recommendation - Proof of Conceptlanguage
dc.typePeer reviewedlanguage
dc.typeJournal article
dc.typeJournal article
dc.date.updated2016-11-08T08:15:46Z
dc.description.versionpublishedVersionlanguage
dc.identifier.cristin1398278


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