Abstract
As one of means for the electronic government embodiment, the website construction and its complement of public sector such as government agency and public institution has been importantly considered. The public sector’s website is operated for public benefit and consequently needs to be continuously redesigned for the users with lower performance in the satisfaction level and effect of using it based on the served information by evaluating whether the performance is different between the users with the various different backgrounds, areas and etc. In this study we present an intelligent evolution model of public sector’s website based on data mining tools in order to improve the whole users’ satisfaction and the effects of using it, especially the users with lower performances by continuously redesigning and complementing the current key web pages.
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Lee, J.A., Jung, J.W.: Strategy for Implementing High Level e-Government based on Customer Relationship Management. Korean National Computerization Agency (2004)
Korean National Computerization Agency.: Guide of construction, operation and information resource management of public institution’s website. Korean National Computerization Agency (1999)
Research group of cyberspace policy of the university of Arizona.: http://w3.arizona.edu
Alesander and Tate.: http://www.widener.edu/wolfgram-memorial-library/inform.htm
Web support group of New Zealand.: http://www.theweb.co.nz/govtweb/0115.html
Kristin, R.E., John, C.B., Charles, R.M., Steven, K.W.: Accessing U.S. Federal Government Websites. Government Information Quarterly 14, 173–189 (1997)
Kohonen, T.: Self-Organization & Associative Memory, 3rd edn. Springer, Berlin (1989)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo (1993)
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© 2005 Springer-Verlag Berlin Heidelberg
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Lee, J.H., Hong, G.H. (2005). Intelligent Website Evolution of Public Sector Based on Data Mining Tools. In: Lowe, D., Gaedke, M. (eds) Web Engineering. ICWE 2005. Lecture Notes in Computer Science, vol 3579. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11531371_37
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DOI: https://doi.org/10.1007/11531371_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27996-9
Online ISBN: 978-3-540-31484-4
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