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Deep Web Crawler: Exploring and Re-ranking of Web Forms

by Rashmi K. B., Vijaya Kumar T., H. S. Guruprasad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 150 - Number 1
Year of Publication: 2016
Authors: Rashmi K. B., Vijaya Kumar T., H. S. Guruprasad
10.5120/ijca2016911448

Rashmi K. B., Vijaya Kumar T., H. S. Guruprasad . Deep Web Crawler: Exploring and Re-ranking of Web Forms. International Journal of Computer Applications. 150, 1 ( Sep 2016), 32-35. DOI=10.5120/ijca2016911448

@article{ 10.5120/ijca2016911448,
author = { Rashmi K. B., Vijaya Kumar T., H. S. Guruprasad },
title = { Deep Web Crawler: Exploring and Re-ranking of Web Forms },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 150 },
number = { 1 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 32-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume150/number1/26059-2016911448/ },
doi = { 10.5120/ijca2016911448 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:54:45.663364+05:30
%A Rashmi K. B.
%A Vijaya Kumar T.
%A H. S. Guruprasad
%T Deep Web Crawler: Exploring and Re-ranking of Web Forms
%J International Journal of Computer Applications
%@ 0975-8887
%V 150
%N 1
%P 32-35
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A huge portion of the web known as deep web is accessible via search interfaces to myriads of databases on the web. Deep web crawl is concerned with the problem of surfacing hidden content behind search interfaces on the web. Given the dynamic nature of the web, where data sources are constantly changing, it is crucial to discover these resources. The paper proposes a two level application namely deep web crawler for gathering relevant searchable forms. In the first level deep web crawler explores the forms based on reverse searching for a given seed site, ranking the sites to prioritize highly relevant sites and by extracting the links to find the forms. In the next level, it searches the forms based on preference and the result is enhanced by re ranking, given the user feedback.

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Index Terms

Computer Science
Information Sciences

Keywords

Deep web adaptive learning ranking

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