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Description
  • Similarity detection is one of the most important areas in document processing. The applications of it starts in spam detection and goes through identification of plagiarism in the web, bachelor or master thesis and ends at identification of copied scientific papers. This paper presents an improvement of a plagiarism detection algorithm which is based on the Lampel and Ziv dictionary based compression algorithm by application of stop words removing and tests this algorithm on real dataset. Moreover, a visualization of the plagiarized documents relationship is also presented. The algorithm confirms its ability in detection of the plagiarized parts of text and also the achieved improvement when the suggested improvements are applied.
  • Similarity detection is one of the most important areas in document processing. The applications of it starts in spam detection and goes through identification of plagiarism in the web, bachelor or master thesis and ends at identification of copied scientific papers. This paper presents an improvement of a plagiarism detection algorithm which is based on the Lampel and Ziv dictionary based compression algorithm by application of stop words removing and tests this algorithm on real dataset. Moreover, a visualization of the plagiarized documents relationship is also presented. The algorithm confirms its ability in detection of the plagiarized parts of text and also the achieved improvement when the suggested improvements are applied. (en)
Title
  • Similarity based on data compression
  • Similarity based on data compression (en)
skos:prefLabel
  • Similarity based on data compression
  • Similarity based on data compression (en)
skos:notation
  • RIV/61989100:27740/13:86088863!RIV14-GA0-27740___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0070), P(EE.2.3.20.0073), P(GPP202/11/P142), 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
  • 105105
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27740/13:86088863
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Visualization; Similarity detection; Plagiarism; Compression (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [271A6E7BBFB4]
http://linked.open...v/mistoKonaniAkce
  • Mexico City
http://linked.open...i/riv/mistoVydani
  • London
http://linked.open...i/riv/nazevZdroje
  • Lecture Notes in Computer Science. Volume 8266
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
  • Platoš, Jan
  • Snášel, Václav
  • Prílepok, Michal
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-45111-9_24
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-45110-2
http://localhost/t...ganizacniJednotka
  • 27740
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