An Approach For Web Data Extraction Based On Similarity Of Templates  

Abstract Category: I.T.
Course / Degree: M.Phil. C.Sc
Institution / University: Prist university, Vallam, Thanjavur, India
Published in: 2013

Thesis Abstract / Summary:

Large amounts of data are available in a large collection of documents from Heterogeneous web pages. Web data extraction has been an important part for many Web data analysis applications. In this thesis, we formulate the data extraction problem based on structured data and tree templates. We propose an unsupervised, page-level data extraction approach to deduce the templates for each individual Deep Website, which contains data records in one Webpage. we use relative path weights to find similarity of underlying template structures in the documents and we cluster the web documents based on the similarity of underlying template structure in the documents so that template is extracted with various clusters. Once the template is identified, the documents are grouped and extracting data is managed through template wrappers. This technique provides better performance compared to previous algorithms in terms of space and time. Our Experimental results with real life data sets confirm effectiveness and robustness of our technique.

Thesis Keywords/Search Tags:
web data extraction, template similarity

This Thesis Abstract may be cited as follows:
Thenmozhi Murugesan, 2013

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Submission Details: Thesis Abstract submitted by thenmozhi murugesh from India on 05-Sep-2013 10:55.
Abstract has been viewed 3413 times (since 7 Mar 2010).

thenmozhi murugesh Contact Details: Email: thenmozhi.murugesh@gmail.com

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