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BURGET, R. BURGETOVÁ, I.
Original Title
Web Page Element Classification Based on Visual Features
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
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.
Keywords
page segmentation, preprocessing, classification, visual features, visual blocks
Authors
BURGET, R.; BURGETOVÁ, I.
RIV year
2009
Released
1. 4. 2009
Publisher
IEEE Computer Society
Location
Dong Hoi
ISBN
978-0-7695-3580-7
Book
1st Asian Conference on Intelligent Information and Database Systems ACIIDS 2009
Pages from
67
Pages to
72
Pages count
6
BibTex
@inproceedings{BUT33776, author="Radek {Burget} and Ivana {Burgetová}", title="Web Page Element Classification Based on Visual Features", booktitle="1st Asian Conference on Intelligent Information and Database Systems ACIIDS 2009", year="2009", pages="67--72", publisher="IEEE Computer Society", address="Dong Hoi", isbn="978-0-7695-3580-7" }