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Description
  • Current multimedia search technology is, especially in commercial applications, heavily based on text annotations. However, there are many applications such as image hosting web sites (e.g. Flickr or Picasa) where the text metadata are of poor quality in general. Searching such collections only by text gives usually rather unsatisfactory results. On the other hand, multimedia retrieval systems based purely on content can retrieve visually similar results but lag behind with the ability to grasp the semantics expressed by text annotations. In this paper, we propose various ranking techniques that can be transparently applied on any content-based retrieval system in order to improve the search results quality and user satisfaction. We demonstrate the usefulness of the approach on two large real-life datasets indexed by the MUFIN system. The improvement of the ranked results was evaluated by real users using an online survey.
  • Current multimedia search technology is, especially in commercial applications, heavily based on text annotations. However, there are many applications such as image hosting web sites (e.g. Flickr or Picasa) where the text metadata are of poor quality in general. Searching such collections only by text gives usually rather unsatisfactory results. On the other hand, multimedia retrieval systems based purely on content can retrieve visually similar results but lag behind with the ability to grasp the semantics expressed by text annotations. In this paper, we propose various ranking techniques that can be transparently applied on any content-based retrieval system in order to improve the search results quality and user satisfaction. We demonstrate the usefulness of the approach on two large real-life datasets indexed by the MUFIN system. The improvement of the ranked results was evaluated by real users using an online survey. (en)
Title
  • Similarity Query Postprocessing by Ranking
  • Similarity Query Postprocessing by Ranking (en)
skos:prefLabel
  • Similarity Query Postprocessing by Ranking
  • Similarity Query Postprocessing by Ranking (en)
skos:notation
  • RIV/00216224:14330/12:00057261!RIV13-GA0-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA201/09/0683), P(GP201/08/P507), P(VF20102014004), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 167880
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/12:00057261
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • ranking; content-based retrieval; metric space (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6CEE1AC97949]
http://linked.open...v/mistoKonaniAkce
  • Linz, Austria
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • Adaptive Multimedia Retrieval. Context, Exploration, and Fusion, LNCS 6817
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Batko, Michal
  • Budíková, Petra
  • Zezula, Pavel
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000306440900012
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-27169-4_12
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 9783642271687
http://localhost/t...ganizacniJednotka
  • 14330
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