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Abstract
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Article Information:
A Feature-Weighted Instance-Based Learner for Deep Web Search Interface Identification
Hong Wang, Qingsong Xu, Youyang Chen and Jinsong Lan
Corresponding Author: Hong Wang
Submitted: June 28, 2012
Accepted: August 08, 2012
Published: February 01, 2013 |
Abstract:
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Determining whether a site has a search interface is a crucial priority for further research of deep web databases. This study first reviews the current approaches employed in search interface identification for deep web databases. Then, a novel identification scheme using hybrid features and a feature-weighted instance-based learner is put forward. Experiment results show that the proposed scheme is satisfactory in terms of classification accuracy and our feature-weighted instance-based learner gives better results than classical algorithms such as C4.5, random forest and KNN.
Key words: Deep web mining, instance-based learning, search interface identification, , , ,
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Cite this Reference:
Hong Wang, Qingsong Xu, Youyang Chen and Jinsong Lan, . A Feature-Weighted Instance-Based Learner for Deep Web Search Interface Identification. Research Journal of Applied Sciences, Engineering and Technology, (04): 1278-1283.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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