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2017 | OriginalPaper | Chapter

A Vision-Based Approach for Deep Web Form Extraction

Authors : Jiachen Pu, Jin Liu, Jin Wang

Published in: Advanced Multimedia and Ubiquitous Engineering

Publisher: Springer Singapore

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Abstract

The World Wide Web is a large source of information that contains data in either Surface Web or Deep Web. Compared with the data in the Surface Web, the Deep Web contains a greater amount of structured data with higher quality, but it is difficult to use directly. Studies in this field have revealed some methods for Deep Web Form Extraction, they may fall into the following categories which are HTML-based, vision-based, ontology-based, ML-based, NLP-based and so on. This paper try to combine the DOM tree and the convolutional neural network together and then find out the form in the Web page. This paper proposed a vision-based method VBF, which figures out the form from the Web page through the acquisition of the HTML code and screenshots of Web pages, establishment of the DOM tree and the calculation of the neural network and form recognition, matching, and generation.

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Metadata
Title
A Vision-Based Approach for Deep Web Form Extraction
Authors
Jiachen Pu
Jin Liu
Jin Wang
Copyright Year
2017
Publisher
Springer Singapore
Book
Advanced Multimedia and Ubiquitous Engineering

Print ISBN: 978-981-10-5040-4

Electronic ISBN: 978-981-10-5041-1

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-5041-1_111

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