DocumentCode
3637592
Title
Text-Based Web Page Classification with Use of Visual Information
Author
Vladimír Bartík
Author_Institution
Dept. of Inf. Syst., Brno Univ. of Technol., Brno, Czech Republic
fYear
2010
Firstpage
416
Lastpage
420
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
"Visualization","Web pages","Classification algorithms","Accuracy","Support vector machine classification","HTML","Equations"
Publisher
ieee
Conference_Titel
Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on
Print_ISBN
978-1-4244-7787-6
Type
conf
DOI
10.1109/ASONAM.2010.34
Filename
5563068
Link To Document