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Description
  • This paper deals with automatic multi-label document classification in the context of a real application for the Czech News Agency. The main goal of this work consists in proposing novel fully unsupervised features based on an unsupervised stemmer, Latent Dirichlet Allocation and semantic spaces (HAL and COALS). The proposed features are integrated into the document classification task. Another interesting contribution is that these two semantic spaces have never been used in the context of document classification before. The proposed approaches are evaluated on a Czech newspaper corpus. We experimentally show that almost all proposed features significantly improve the document classification score. The corpus is freely available for research purposes.
  • This paper deals with automatic multi-label document classification in the context of a real application for the Czech News Agency. The main goal of this work consists in proposing novel fully unsupervised features based on an unsupervised stemmer, Latent Dirichlet Allocation and semantic spaces (HAL and COALS). The proposed features are integrated into the document classification task. Another interesting contribution is that these two semantic spaces have never been used in the context of document classification before. The proposed approaches are evaluated on a Czech newspaper corpus. We experimentally show that almost all proposed features significantly improve the document classification score. The corpus is freely available for research purposes. (en)
Title
  • Novel Unsupervised Features for Czech Multi-label Document Classification
  • Novel Unsupervised Features for Czech Multi-label Document Classification (en)
skos:prefLabel
  • Novel Unsupervised Features for Czech Multi-label Document Classification
  • Novel Unsupervised Features for Czech Multi-label Document Classification (en)
skos:notation
  • RIV/49777513:23520/14:43924209!RIV15-MSM-23520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0090), 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
  • 33134
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/14:43924209
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Maximum Entropy; Czech News Agency; Czech; Stemming; HPS; COALS; HAL; Semantic spaces; LDA; Multi-label Document Classification (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [5152F8EB408B]
http://linked.open...v/mistoKonaniAkce
  • Tuxtla Gutiérrez, Mexico
http://linked.open...i/riv/mistoVydani
  • Heidelberg
http://linked.open...i/riv/nazevZdroje
  • Human-Inspired Computing and Its Applications
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
  • Král, Pavel
  • Brychcín, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-319-13647-9_8
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-319-13646-2
http://localhost/t...ganizacniJednotka
  • 23520
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