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  • Existing anti-plagiarism tools are, in fact, text matching systems but do not make accurate judgments about plagiarism. Texts that are acceptable to be redundant and texts that are cited properly are all highlighted as plagiarism, and the real decision of plagiarism is left up to the user. To reduce the human input and to give more reliance to automatic plagiarism detectors, we propose an Intelligent Plagiarism Reasoner (iPlag), which works by combining several analytical procedures. Scholarly documents under investigation are segmented into logical tree-structured representation using a procedure called D-SEGMENT. Statistical methods are utilised to assign numerical weights to structural components under a technique called C-WEIGHT. Relevance ranking (R-RANK) and plagiarism screening approaches (P-SCREEN) are adjusted to incorporate structural weights, citation evidences, syntax-based and semantic-based methods into plagiarism detection results. We encourage current plagiarism detection systems to adapt the proposed framework. 2011 IEEE.
  • Existing anti-plagiarism tools are, in fact, text matching systems but do not make accurate judgments about plagiarism. Texts that are acceptable to be redundant and texts that are cited properly are all highlighted as plagiarism, and the real decision of plagiarism is left up to the user. To reduce the human input and to give more reliance to automatic plagiarism detectors, we propose an Intelligent Plagiarism Reasoner (iPlag), which works by combining several analytical procedures. Scholarly documents under investigation are segmented into logical tree-structured representation using a procedure called D-SEGMENT. Statistical methods are utilised to assign numerical weights to structural components under a technique called C-WEIGHT. Relevance ranking (R-RANK) and plagiarism screening approaches (P-SCREEN) are adjusted to incorporate structural weights, citation evidences, syntax-based and semantic-based methods into plagiarism detection results. We encourage current plagiarism detection systems to adapt the proposed framework. 2011 IEEE. (en)
Title
  • iPlag: Intelligent plagiarism reasoner in scientific publications
  • iPlag: Intelligent plagiarism reasoner in scientific publications (en)
skos:prefLabel
  • iPlag: Intelligent plagiarism reasoner in scientific publications
  • iPlag: Intelligent plagiarism reasoner in scientific publications (en)
skos:notation
  • RIV/61989100:27240/11:86092968!RIV15-MSM-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
  • Abraham Padath, Ajith
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 205806
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/11:86092968
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • semantic; scientific publications; plagiarism detection; intelligent reasoner (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [A110E51E2662]
http://linked.open...v/mistoKonaniAkce
  • Mumbai
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 2011 World Congress on Information and Communication Technologies, WICT 2011
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Abraham Padath, Ajith
  • Alzahrani, S.
  • Palade, V.
  • Salim, N.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/WICT.2011.6141191
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-1-4673-0125-1
http://localhost/t...ganizacniJednotka
  • 27240
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