DocumentCode :
1868452
Title :
Internet based industry community discovery and its applications to industry survey
Author :
Zou Xiaojun ; Zhang Hua ; Hu Junfeng
Author_Institution :
School of Electronics Engineering & Computer Science, Peking University, China
fYear :
2012
fDate :
3-5 March 2012
Firstpage :
1255
Lastpage :
1259
Abstract :
With the deepening of social informatization, almost every aspect of the key industries of national economy is reflected on the internet, such as industrial structure, industrial distribution, industrial-scale, industrial development, industrial policies and so on. How to use these massive free industrial data on the internet effectively becomes more and more important for industrial rule exploration and industrial policy formulation. Industry is a concept between microeconomic cells and macroscopical economy units. If each microeconomic cell is viewed as a node in networks, then the whole national economy constitutes a complex network, and further, a specific industry is a community of this complex network. In this paper, we propose the concept of internet based industry community and two discovery algorithms, and then apply them to industry survey. The case study on fishing industry shows that internet based industry community can offer constructive information in tasks such as comparative analysis of domestic and foreign industries and hot events tracking.
Keywords :
Community Discovery; Complex Network; Industry Community; Industry Survey;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on
Conference_Location :
Xiamen
Electronic_ISBN :
978-1-84919-537-9
Type :
conf
DOI :
10.1049/cp.2012.1207
Filename :
6492814
Link To Document :
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