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Description
  • The paper describes experiments that used Genetic Algorithms for looking for important word assocoations (phrases) in unstructured text documents obtained from the Internet in the area of a specialized medicine branch. Genetic alforithms can evolve sets of word associations with assigned significance weights from the document categorization point of view (relevant and irrelevant documents). The categorization is similarly reliable like the naive Bayes classification based on individual words. In addition, genetic algorithms provided phrases consisting of one, two, and three words. The phrases were quite meaningful from the human point of view.
  • The paper describes experiments that used Genetic Algorithms for looking for important word assocoations (phrases) in unstructured text documents obtained from the Internet in the area of a specialized medicine branch. Genetic alforithms can evolve sets of word associations with assigned significance weights from the document categorization point of view (relevant and irrelevant documents). The categorization is similarly reliable like the naive Bayes classification based on individual words. In addition, genetic algorithms provided phrases consisting of one, two, and three words. The phrases were quite meaningful from the human point of view. (en)
  • The paper describes experiments that used Genetic Algorithms for looking for important word assocoations (phrases) in unstructured text documents obtained from the Internet in the area of a specialized medicine branch. Genetic alforithms can evolve sets of word associations with assigned significance weights from the document categorization point of view (relevant and irrelevant documents). The categorization is similarly reliable like the naive Bayes classification based on individual words. In addition, genetic algorithms provided phrases consisting of one, two, and three words. The phrases were quite meaningful from the human point of view. (cs)
Title
  • Searching for Significant Word Associations in Text Documents Using Genetic Algorithms
  • Searching for Significant Word Associations in Text Documents Using Genetic Algorithms (en)
  • Searching for Significant Word Associations in Text Documents Using Genetic Algorithms (cs)
skos:prefLabel
  • Searching for Significant Word Associations in Text Documents Using Genetic Algorithms
  • Searching for Significant Word Associations in Text Documents Using Genetic Algorithms (en)
  • Searching for Significant Word Associations in Text Documents Using Genetic Algorithms (cs)
skos:notation
  • RIV/00216224:14330/03:00009148!RIV08-MSM-14330___
http://linked.open.../vavai/riv/strany
  • 584-587
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
  • 626493
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/03:00009148
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • machine learning; text document processing; genetic algorithms; naive Bayes method (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [8040803853C7]
http://linked.open...v/mistoKonaniAkce
  • Mexico City, Mexico
http://linked.open...i/riv/mistoVydani
  • Berlin Heidelberg New York
http://linked.open...i/riv/nazevZdroje
  • Computional 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
  • Šrédl, Michal
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
https://schema.org/isbn
  • 3-540-00532-3
http://localhost/t...ganizacniJednotka
  • 14330
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