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Research on E-Government Knowledge Navigation System Based on XTM
Hong Kong, China December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI-IATW.2006.1112006 IEEE/WIC/ACM International Confe ...
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Jiangnan Qiu, Yongxiang Yao, Yanzhang Wang, Xuehua Wang, "Research on E-Government Knowledge Navigation System Based on XTM," Web Intelligence and Intelligent Agent Technology, International Conference on, pp. 586-589, 2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2006.
 
 
BibTex
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@article{ 10.1109/WI-IATW.2006.111,
author = {Jiangnan Qiu and Yongxiang Yao and Yanzhang Wang and Xuehua Wang},
title = {Research on E-Government Knowledge Navigation System Based on XTM},
journal ={Web Intelligence and Intelligent Agent Technology, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2749-3},
pages = {586-589},
doi = {http://doi.ieeecomputersociety.org/10.1109/WI-IATW.2006.111},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Web Intelligence and Intelligent Agent Technology, International Conference on
TI - Research on E-Government Knowledge Navigation System Based on XTM
SN - 0-7695-2749-3
SP586
EP589
A1 - Jiangnan Qiu,
A1 - Yongxiang Yao,
A1 - Yanzhang Wang,
A1 - Xuehua Wang,
PY - 2006
KW - null
VL - 0
JA - Web Intelligence and Intelligent Agent Technology, International Conference on
ER -
 
Jiangnan Qiu, Dalian University of Technology, China
Yongxiang Yao, Dalian University of Technology, China
Yanzhang Wang, Dalian University of Technology, China
Xuehua Wang, Dalian University of Technology, China
Against problem on current Government Portal navigation system is mostly based on keyword. An XTM-based E-Government knowledge navigation system model was proposed, and a XTM based association and occurrences measurement mechanism is imported to the system. Especially based on analyses of topic relative semantic structure, a tree-structure semantic architecture is extracted from XTM by dividing the type of topic association. Semantics relatedness is introduced in the article to expand the second level association and calculate the degree of topic relative. The results show that the system has a good effectiveness and efficiency of navigation.
Citation:
Jiangnan Qiu, Yongxiang Yao, Yanzhang Wang, Xuehua Wang, "Research on E-Government Knowledge Navigation System Based on XTM," wi-iatw, pp.586-589, 2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2006
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