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  • In this article, we would like to present new approach to classification with Linked Data and PageRank. Our research is focused on classification methods that are enhanced by semantic information. The semantic information can be obtained from ontology or from Linked Data. DBpedia was used as source of Linked Data in our case. Feature selection method is semantically based so features can be recognized by nonprofessional users because they are in a human readable and understandable form. PageRank is used during feature selection and generation phase for expansion of basic features into more general representatives. It means that feature selection and processing is based on a network relations obtained from Linked Data. The features can be used by standard classification algorithms. We will present the promising preliminary results that show the easy applicability of this approach to different datasets.
  • In this article, we would like to present new approach to classification with Linked Data and PageRank. Our research is focused on classification methods that are enhanced by semantic information. The semantic information can be obtained from ontology or from Linked Data. DBpedia was used as source of Linked Data in our case. Feature selection method is semantically based so features can be recognized by nonprofessional users because they are in a human readable and understandable form. PageRank is used during feature selection and generation phase for expansion of basic features into more general representatives. It means that feature selection and processing is based on a network relations obtained from Linked Data. The features can be used by standard classification algorithms. We will present the promising preliminary results that show the easy applicability of this approach to different datasets. (en)
Title
  • Linked Data and pageRank based classification
  • Linked Data and pageRank based classification (en)
skos:prefLabel
  • Linked Data and pageRank based classification
  • Linked Data and pageRank based classification (en)
skos:notation
  • RIV/49777513:23520/13:43919410!RIV14-MSM-23520___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0090), P(GAP103/11/1489)
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
  • 85038
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/13:43919410
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • feature selection; PageRank; Linked Data; classification (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D2D771F78D9E]
http://linked.open...v/mistoKonaniAkce
  • Praha
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the IADIS International conference Theory and Practice in Modern Computing 2013
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
  • Dostal, Martin
  • Ježek, Karel
  • Fiala, Dalibor
  • Nykl, Michal
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • IADIS Press
https://schema.org/isbn
  • 978-972-8939-94-6
http://localhost/t...ganizacniJednotka
  • 23520
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