Detail publikace

Text-Based Web Page Classification with Use of Visual Information

Originální název

Text-Based Web Page Classification with Use of Visual Information

Anglický název

Text-Based Web Page Classification with Use of Visual Information

Jazyk

en

Originální abstrakt

As the number of pages on the web is permanently increasing, there is a need to classify pages into categories to facilitate indexing or searching them. In the method proposed here, we use both textual and visual information to find a suitable representation of web page content. In this paper, several term weights, based on TF or TF-IDF weighting are proposed. Modification is based on visual areas, in which the text appears and their visual properties. Some results of experiments are included in the final part of the paper.

Anglický abstrakt

As the number of pages on the web is permanently increasing, there is a need to classify pages into categories to facilitate indexing or searching them. In the method proposed here, we use both textual and visual information to find a suitable representation of web page content. In this paper, several term weights, based on TF or TF-IDF weighting are proposed. Modification is based on visual areas, in which the text appears and their visual properties. Some results of experiments are included in the final part of the paper.

BibTex


@inproceedings{BUT35625,
  author="Vladimír {Bartík}",
  title="Text-Based Web Page Classification with Use of Visual Information",
  annote="As the number of pages on the web is permanently increasing, there is a need to
classify pages into categories to facilitate indexing or searching them. In the
method proposed here, we use both textual and visual information to find
a suitable representation of web page content. In this paper, several term
weights, based on TF or TF-IDF weighting are proposed. Modification is based on
visual areas, in which the text appears and their visual properties. Some results
of experiments are included in the final part of the paper.",
  address="IEEE Computer Society",
  booktitle="2010 International Conference on Advances in Social Network Analysis and Mining",
  chapter="35625",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Computer Society",
  year="2010",
  month="august",
  pages="416--420",
  publisher="IEEE Computer Society",
  type="conference paper"
}