• 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