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Description
  • Článek popisuje problémy s klasifikací a filtrací podobných relevantních a nerelevantních reálných textových dokumentů z jedné velmi specifické domény, získané z internetových zdrojů. Kromě podobnosti jsou dokumenty často nevyváženy -- nedostatek nerelevantních dokumentů pro trénování. Je navržena definice podobnosti. Klasifikace byla testována pomocí šesti algoritmů z hlediska podobnosti textů. Nejlepší výsledky poskytly neuronové sítě založené na backpropagation a support vector machines s radiálními bázovými funkcemi. (cs)
  • This paper describes problems with classification and filtration of similar relevant and irrelevant real medical documents from one very specific domain, obtained from the Internet resources. Besides the similarity, the documents are often unbalanced-a lack of irrelevant documents for the training. A definition of similarity is suggested. For the classification, six algorithms are tested from the document similarity point of view. The best results are provided by the back propagation-based neural network and by the radial basis function-based support vector machine.
  • This paper describes problems with classification and filtration of similar relevant and irrelevant real medical documents from one very specific domain, obtained from the Internet resources. Besides the similarity, the documents are often unbalanced-a lack of irrelevant documents for the training. A definition of similarity is suggested. For the classification, six algorithms are tested from the document similarity point of view. The best results are provided by the back propagation-based neural network and by the radial basis function-based support vector machine. (en)
Title
  • Filtering Very Similar Text Documents: A Case Study
  • Filtering Very Similar Text Documents: A Case Study (en)
  • Filtrace velmi podobných textových dokumentů: Studie případu. (cs)
skos:prefLabel
  • Filtering Very Similar Text Documents: A Case Study
  • Filtering Very Similar Text Documents: A Case Study (en)
  • Filtrace velmi podobných textových dokumentů: Studie případu. (cs)
skos:notation
  • RIV/00216224:14330/04:00009948!RIV08-MSM-14330___
http://linked.open.../vavai/riv/strany
  • 511-520
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM 143300003)
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
  • 564379
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/04:00009948
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • machine learning; text categorization; text filtration; text similarity (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [45505C6B08EC]
http://linked.open...v/mistoKonaniAkce
  • Seoul, Korea
http://linked.open...i/riv/mistoVydani
  • Germany
http://linked.open...i/riv/nazevZdroje
  • Computational linguistics and Intelligent Text Processing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Žižka, Jan
  • Bourek, Aleš
  • Hroza, Jiří
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag. (Berlin; Heidelberg)
https://schema.org/isbn
  • 3-540-21006-7
http://localhost/t...ganizacniJednotka
  • 14330
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