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Collaborative identification and annotation of government deep web resources: a hybrid approach

Published: 13 June 2010 Publication History

Abstract

In this extended abstract, we propose a hybrid approach of automatic means and social computing to identify and annotate Deep Web resources - mainly databases and database portals - to provide easy access to and descriptions and instruction on how to use these resources.

References

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Selby, B. 2008. Age of Aquarius-The FDLP in the 21st century. Government Information Quarterly, 25, 1 (2008), 38--47.
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Bertot, J. C. and Jaeger, P. T. 2008. The E-Government paradox: Better customer service doesn't necessarily cost less. Government Information Quarterly, 25, 2 (2008), 149--154.
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He, B., Patel, M., Zhang, Z. and Chang, K. C.-C. 2007. Accessing the deep web. Commun. ACM, 50, 5 (2007), 94--101.
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Kittur, A., Chi, E., & Suh, B. 2008. Crowdsourcing User Studies with Mechanical Turk. CHI '08. 1, 453-456.
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Cope, J., Craswell, N. and Hawking, D. 2003. Automated discovery of search interfaces on the web. In Proceedings of the 14th Australasian database conference, Adelaide, Australia, 2003.
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Barbosa, L. and Freire, J. Combining classifiers to identify online databases. 2007. In Proceedings of the 16th international conference on World Wide Web (Banff, Alberta, Canada, 2007).
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Hess, A. and Kushmerick, N. 2003. Learning to attach semantic metadata to web services. Springer Berlin / Heidelberg, 2003

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  • (2013)Automatic discovery of Web Query Interfaces using machine learning techniquesJournal of Intelligent Information Systems10.1007/s10844-012-0217-440:1(85-108)Online publication date: 1-Feb-2013

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  1. Collaborative identification and annotation of government deep web resources: a hybrid approach

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    cover image ACM Conferences
    HT '10: Proceedings of the 21st ACM conference on Hypertext and hypermedia
    June 2010
    328 pages
    ISBN:9781450300414
    DOI:10.1145/1810617

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 June 2010

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    Author Tags

    1. collaborative identification and annotation
    2. government databases
    3. hybrid approach
    4. social computing

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    HT '10
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    HT '10: 21st ACM Conference on Hypertext and Hypermedia
    June 13 - 16, 2010
    Ontario, Toronto, Canada

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    Overall Acceptance Rate 378 of 1,158 submissions, 33%

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    • (2013)Automatic discovery of Web Query Interfaces using machine learning techniquesJournal of Intelligent Information Systems10.1007/s10844-012-0217-440:1(85-108)Online publication date: 1-Feb-2013

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