Publication detail

Text-Based Web Page Classification with Use of Visual Information

BARTÍK, V.

Original Title

Text-Based Web Page Classification with Use of Visual Information

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

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.

Keywords

web page classification, term weights, text classification, TF-IDF weight, visual information, visual  blocks

Authors

BARTÍK, V.

RIV year

2010

Released

13. 8. 2010

Publisher

IEEE Computer Society

Location

Odense

ISBN

978-0-7695-4138-9

Book

2010 International Conference on Advances in Social Network Analysis and Mining

Pages from

416

Pages to

420

Pages count

5

BibTex

@inproceedings{BUT35625,
  author="Vladimír {Bartík}",
  title="Text-Based Web Page Classification with Use of Visual Information",
  booktitle="2010 International Conference on Advances in Social Network Analysis and Mining",
  year="2010",
  pages="416--420",
  publisher="IEEE Computer Society",
  address="Odense",
  isbn="978-0-7695-4138-9"
}