Volume 5 Number 7 (Jul. 2010)
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JSW 2010 Vol.5(7): 713-720 ISSN: 1796-217X
doi: 10.4304/jsw.5.7.713-720

Ontology Based Automatic Attributes Extracting and Queries Translating for Deep Web

Hao Liang1, 2, Fei Ren3, WanLi Zuo1, 4, FengLing He1, 4

1College of Computer Science and Technology, Jilin University, Changchun 130012, China
2Department of Information, Changchun Taxation College, Changchun 130117, China
3China Development Bank, Center of Operations, Beijing, 100037, China
4Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun, 130012, China

Abstract—Search engines and web crawlers can not access the Deep Web directly. The workable way to access the hidden database is through query interfaces. Automatic extracting attributes from query interfaces and translating queries is a solvable way for addressing the current limitations in accessing Deep Web. However, the query interface provides semantic constraints, some attributes are co-occurred and the others are exclusive sometimes. To generate a valid query, we have to reconcile the key attributes and semantic relation between them. We design a framework to automatically extract attributes from query interfaces taking full advantage of instances information and enrich the attribute sets embedded in the semantic query interface by Ontology technique. Each attribute is extended into a candidate attribute expressed by a hierarchy tree and describes the semantic relation of the attributes. We carry out our experiments in the real-world domain and results showed the validation of query translation framework.

Index Terms—Deep Web, Surface Web, query interface, WordNet, Ontology, hierarchy tree.

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Cite: Hao Liang, Fei Ren, WanLi Zuo, FengLing He, "Ontology Based Automatic Attributes Extracting and Queries Translating for Deep Web," Journal of Software vol. 5, no. 7, pp. 713-720, 2010.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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