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dc.contributor.authorSkorkovská, Lucie
dc.date.accessioned2015-12-17T11:02:33Z
dc.date.available2015-12-17T11:02:33Z
dc.date.issued2014
dc.identifier.citationSKORKOVSKÁ, Lucie. First experiments with relevant documents selection for blind relevance feedback in spoken document retrieval. In: Proceedings 16th International Conference, SPECOM 2014, Novi Sad, Serbia, 5-9 October, 2014. Berlin: Springer, 2014, p. 235-242. (Lectures notes in computer science; 8773). ISBN 978-3-319-11580-1.en
dc.identifier.isbn978-3-319-11580-1
dc.identifier.urihttp://www.kky.zcu.cz/cs/publications/LucieSkorkovska_2014_FirstExperiments
dc.identifier.urihttp://hdl.handle.net/11025/17047
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofseriesLecture notes in computer science; 8773en
dc.rights© Lucie Skorkovskács
dc.subjectrozšíření dotazucs
dc.subjectautomatická zpětná vazbacs
dc.subjectvyhledávání informací v řečics
dc.subjectscore normalizationcs
dc.titleFirst experiments with relevant documents selection for blind relevance feedback in spoken document retrievalen
dc.title.alternativePrvní experimenty se selekcí relevantních dokumentů pro zpětnou vazbu ve vyhledávání informací v řečics
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThis paper presents our first experiments aimed at the automatic selection of the relevant documents for the blind relevance feedback method in speech information retrieval. Usually the relevant documents are selected only by simply determining the first N documents to be relevant. We consider this approach to be insufficient and we would try in this paper to outline the possibilities of the dynamical selection of the relevant documents for each query depending on the content of the retrieved documents instead of just blindly defining the number of the relevant documents to be used for the blind relevance feedback in advance. We have performed initial experiments with the application of the score normalization techniques used in the speaker identification task, which was successfully used in the multi-label classification task for finding the “correct” topics of a newspaper article in the output of a generative classifier. The experiments have shown promising results, therefore they will be used to define the possibilities of the subsequent research in this area.en
dc.subject.translatedquery expansionen
dc.subject.translatedblind relevance feedbacken
dc.subject.translatedspoken document retrievalen
dc.subject.translatednormalizace skóreen
dc.identifier.doi10.1007/978-3-319-11581-8_29
dc.type.statusPeer-revieweden
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