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2009 International Conference on Business Intelligence and Financial Engineering
A New Research Field: Intelligent Knowledge Management
Beijing, China
July 24-July 26
ISBN: 978-0-7695-3705-4
ASCII Text
x 
 
Lingling Zhang, Jun Li, Aihua Li, Peng Zhang, Guangli Nie, Yong Shi, "A New Research Field: Intelligent Knowledge Management," Business Intelligence and Financial Engineering, International Conference on, pp. 450-454, 2009 International Conference on Business Intelligence and Financial Engineering, 2009.
 
 
BibTex
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@article{ 10.1109/BIFE.2009.108,
author = {Lingling Zhang and Jun Li and Aihua Li and Peng Zhang and Guangli Nie and Yong Shi},
title = {A New Research Field: Intelligent Knowledge Management},
journal ={Business Intelligence and Financial Engineering, International Conference on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3705-4},
pages = {450-454},
doi = {http://doi.ieeecomputersociety.org/10.1109/BIFE.2009.108},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Business Intelligence and Financial Engineering, International Conference on
TI - A New Research Field: Intelligent Knowledge Management
SN - 978-0-7695-3705-4
SP450
EP454
A1 - Lingling Zhang,
A1 - Jun Li,
A1 - Aihua Li,
A1 - Peng Zhang,
A1 - Guangli Nie,
A1 - Yong Shi,
PY - 2009
KW - data
KW - data mining
KW - knowledge management
KW - intelligent knowledge
KW - intelligent knowledge management
VL - 0
JA - Business Intelligence and Financial Engineering, International Conference on
ER -
 
Knowledge or hidden patterns discovered by data mining from large-scale databases has great novelty, which is often unable to be gained from the experts. Given large-scale databases, this paper proposes foundations of intelligent knowledge management. It enables to generate "special" knowledge, called intelligent knowledge base on the hidden patterns created by data mining. Furthermore, this paper systematically analyzes the process of intelligent knowledge management – a new proposition from original data, rough knowledge, intelligent knowledge, and actionable knowledge as well as the four transformations (4T) of these items. This study not only promotes more significant research beyond data mining, but also enhances the quantitative analysis of knowledge management on hidden patterns from data mining.
Index Terms:
data, data mining, knowledge management, intelligent knowledge, intelligent knowledge management
Citation:
Lingling Zhang, Jun Li, Aihua Li, Peng Zhang, Guangli Nie, Yong Shi, "A New Research Field: Intelligent Knowledge Management," bife, pp.450-454, 2009 International Conference on Business Intelligence and Financial Engineering, 2009
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