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Reseach Article

A Novel Approach for Automatic Data Extraction from Heterogeneous Web Pages

Published on January 2012 by Teena Merin Thomas, V. Vidhya
Emerging Technology Trends on Advanced Engineering Research - 2012
Foundation of Computer Science USA
ICETT - Number 3
January 2012
Authors: Teena Merin Thomas, V. Vidhya
c3c7ae6f-5083-49a5-bdca-8c8b909fd090

Teena Merin Thomas, V. Vidhya . A Novel Approach for Automatic Data Extraction from Heterogeneous Web Pages. Emerging Technology Trends on Advanced Engineering Research - 2012. ICETT, 3 (January 2012), 24-28.

@article{
author = { Teena Merin Thomas, V. Vidhya },
title = { A Novel Approach for Automatic Data Extraction from Heterogeneous Web Pages },
journal = { Emerging Technology Trends on Advanced Engineering Research - 2012 },
issue_date = { January 2012 },
volume = { ICETT },
number = { 3 },
month = { January },
year = { 2012 },
issn = 0975-8887,
pages = { 24-28 },
numpages = 5,
url = { /proceedings/icett/number3/9845-1025/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Emerging Technology Trends on Advanced Engineering Research - 2012
%A Teena Merin Thomas
%A V. Vidhya
%T A Novel Approach for Automatic Data Extraction from Heterogeneous Web Pages
%J Emerging Technology Trends on Advanced Engineering Research - 2012
%@ 0975-8887
%V ICETT
%N 3
%P 24-28
%D 2012
%I International Journal of Computer Applications
Abstract

World Wide Web is a vast and rapidly growing source of information. Web Pages contain a combination of unique data and template material, which is present across multiple pages to achieve high productivity of publishing. The template detection becomes a more attractive technique in the web pages, since the unknown template degrade the performance of web applications due to the irrelevant terms in the templates. The web pages is clustered using Agglomerative Clustering Algorithm based on the similarity of templates in the web pages. The unknown number of web pages and the partitioning of web pages is dealt with the help of Rissanen's Minimum Description Length Principle. Wrappers are generated for clustered heterogeneous web pages and the data encoded in the web pages are automatically extracted. Hence, the proposed approach for automatic data extraction let the web page users to access the data in a quick and easiest manner with better effectiveness and scalability.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Wrap_match Mdl Clustering Essential Paths