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DOI: 10.2298/CSIS100322028W

Research on Discovering Deep Web Entries

Ying Wang^1,2, Huilai Li³, Wanli Zuo^1,2, Fengling He^1,2, Xin Wang^1,4 and Kerui Chen^1,2

1. College of Computer Science and Technology, Jilin University
   130012 Changchun, China
2. Key Laboratory of Computation and Knowledge Engineering,
   Ministry of Education, China
   {wangying2010, zuowl, hefl}@jlu.edu.cn, Chenke0616@163.com
3. College of Mathematics, Jilin University
   130012 Changchun, China
   lihuilai@jlu.edu.cn
4. College of Software, Changchun Institute of Technology,
   130012 Changchun, China
   wangxccs@126.com

Abstract

Ontology plays an important role in locating Domain-Specific Deep Web contents, therefore, this paper presents a novel framework WFF for efficiently locating Domain-Specific Deep Web databases based on focused crawling and ontology by constructing Web Page Classifier(WPC), Form Structure Classifier(FSC) and Form Content Classifier(FCC) in a hierarchical fashion. Firstly, WPC discovers potentially interesting pages based on ontology-assisted focused crawler. Then, FSC analyzes the interesting pages and determines whether these pages subsume searchable forms based on structural characteristics. Lastly, FCC identifies searchable forms that belong to a given domain in the semantic level, and stores these URLs of Domain-Specific searchable forms to a database. Through a detailed experimental evaluation, WFF framework not only simplifies discovering process, but also effectively determines Domain-Specific databases.

Key words

Deep Web, ontology, WPC, FSC, FCC

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS100322028W

Publication information

Volume 8, Issue 3 (June 2011)
Year of Publication: 2011
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Wang, Y., Li, H., Zuo, W., He, F., Wang, X., Chen, K.: Research on Discovering Deep Web Entries. Computer Science and Information Systems, Vol. 8, No. 3, 779-799. (2011), https://doi.org/10.2298/CSIS100322028W