Research on discovering deep web entries | Zendy

Ying Wang | Zendy; Huilai Li | Zendy; Wanli Zuo | Zendy; Fengling He | Zendy; Xin Wang | Zendy; Kerui Chen | Zendy

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Research on discovering deep web entries

Author(s) -

Ying Wang,

Huilai Li,

Wanli Zuo,

Fengling He,

Xin Wang,

Kerui Chen

Publication year - 2011

Publication title -

computer science and information systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.244

H-Index - 24

eISSN - 2406-1018

pISSN - 1820-0214

DOI - 10.2298/csis100322028w

Subject(s) - computer science , web crawler , information retrieval , classifier (uml) , crawling , web page , ontology , domain (mathematical analysis) , semantic web , deep web , world wide web , focused crawler , artificial intelligence , static web page , the internet , web navigation , medicine , mathematical analysis , philosophy , mathematics , epistemology , anatomy

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.

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