About: Automatic annotation of online articles based on visual feature classification     Goto   Sponge   NotDistinct   Permalink

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Description
  • When applying the traditional data mining methods to World Wide Web documents, the typical problem is that a normal web page contains a variety of information of different kinds in addition to its main content. This additional information such as navigation, advertisement or copyright notices negatively influences the results of the data mining methods as for example the content classification. In this paper, we present a method of interesting area detection in a web page. This method is inspired by an assumed human reader approach to this task. First, basic visual blocks are detected in the page and subsequently, the purpose of these blocks is guessed based on their visual appearance. We describe a page segmentation method used for the visual block detection, we propose a way of the block classification based on the visual features and finally, we provide an experimental evaluation of the method on real-world data.
  • When applying the traditional data mining methods to World Wide Web documents, the typical problem is that a normal web page contains a variety of information of different kinds in addition to its main content. This additional information such as navigation, advertisement or copyright notices negatively influences the results of the data mining methods as for example the content classification. In this paper, we present a method of interesting area detection in a web page. This method is inspired by an assumed human reader approach to this task. First, basic visual blocks are detected in the page and subsequently, the purpose of these blocks is guessed based on their visual appearance. We describe a page segmentation method used for the visual block detection, we propose a way of the block classification based on the visual features and finally, we provide an experimental evaluation of the method on real-world data. (en)
Title
  • Automatic annotation of online articles based on visual feature classification
  • Automatic annotation of online articles based on visual feature classification (en)
skos:prefLabel
  • Automatic annotation of online articles based on visual feature classification
  • Automatic annotation of online articles based on visual feature classification (en)
skos:notation
  • RIV/00216305:26230/11:PU96111!RIV12-MSM-26230___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S, Z(MSM0021630528)
http://linked.open...iv/cisloPeriodika
  • 4
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
  • 187554
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/11:PU96111
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • automatic annotation, online articles, page segmentation, document preprocessing, visual features, visual analysis, data mining, classification (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CH - Švýcarská konfederace
http://linked.open...ontrolniKodProRIV
  • [88482FF002BE]
http://linked.open...i/riv/nazevZdroje
  • International Journal of Intelligent Information and Database System
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 5
http://linked.open...iv/tvurceVysledku
  • Burget, Radek
  • Burgetová, Ivana
http://linked.open...n/vavai/riv/zamer
issn
  • 1751-5858
number of pages
http://localhost/t...ganizacniJednotka
  • 26230
is http://linked.open...avai/riv/vysledek of
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