Abstract
Deep Web contains a significant amount of visited information, in order to effectively guide users to the appropriate searchable web databases, we need to organize it according to different domain. Ontology plays an important role in locating Deep Web content, therefore, this paper proposes a new Deep Web database selection framework based on ontology. Firstly, constructing domain ontology content model (DOCM), and then, designing the ontology-assisted similarity algorithm, which adds semantic information to form eigenvectors, lastly, selecting the mapping relational databases as domain-specific databases. Experiment shows that the method can effectively select Deep Web databases.
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References
Ru, Y., Horowitz, E.: Indexing the Invisible Web: A Survey. Online Information Review 29(3), 249–265 (2005)
Barbosa, L., Freire, J.: Combining Classifiers to Identify Online Databases. In: Proceedings of the World Wide Web Conference (www), pp. 431–440 (2007)
Ipeirotis, P.G., Gravano, L.: Classification-Aware Hidden-Web Text Database Selection. ACM Transactions on Information Systems (2008)
Lau, A., Tsui, E., Lee, W.B.: An Ontology-based Similarity Measurement for Problem-based Case Reasoning. Expert Systems with Applications 36(3), 6574–6579 (2009)
Su, W., Wang, J., Lochovsky, F.H.: ODE: Ontology-assisted Data Extraction. ACM Transactions on Database Systems 34(2), 1–35 (2009)
Zhang, W., Yoshida, T., Tang, X.: Using Ontology to Improve Precision of Terminology Extraction from Documents. Expert System with Applications, 9333–9339 (2009)
Horridge, M., Parsia, B., Sattler, U.: Explanation of OWL Entailments in Protege4. In: Proceedings of International Semantic Web Conference (2008)
Hong, J., He, Z., Bell, D.A.: An Evidential Approach to Query Interface Matching on the Deep Web. Journal of Information System 35(2), 140–148 (2010)
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© 2011 Springer-Verlag Berlin Heidelberg
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Wang, Y., Zuo, W., He, F., Wang, X., Zhang, A. (2011). Ontology-Assisted Deep Web Source Selection. In: Yu, Y., Yu, Z., Zhao, J. (eds) Computer Science for Environmental Engineering and EcoInformatics. CSEEE 2011. Communications in Computer and Information Science, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22691-5_12
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DOI: https://doi.org/10.1007/978-3-642-22691-5_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22690-8
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