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Evolution Analysis of Online Knowledge Transfer Network

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Information Computing and Applications (ICICA 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 391))

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Abstract

Based on the study of online knowledge transfer network‘s topology and dynamic statistical characteristics, this paper found the characteristic differences between the evolution of online knowledge transfer network and the traditional BA network model. Through the empirical data analysis of a BBS forum, it gives out an evolution model of the online knowledge transfer network based on the PageRank algorithm. Meanwhile, in the network analysis it also found that the network growth model has a power-law distribution of degree. Through the control of the attenuation coefficient and the node degree growth factor, it can ultimately realize growth control of the online knowledge transfer network.

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Author information

Authors and Affiliations

  1. College of Economic and Management, Nanjing University of Post and Telecommunication, Nanjing, 210046, China

    Jing Wei

  2. College of Economic and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Ruixiao Song, Jianjun Miao & Zan Xu

Authors
  1. Jing Wei
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  2. Ruixiao Song
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  3. Jianjun Miao
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  4. Zan Xu
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Editor information

Editors and Affiliations

  1. Shanghai Jiao Tong University, 800 Dongchuan Road, Dianxinqunlou 1-401, 200240, Shanghai, China

    Yuhang Yang

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore, Singapore

    Maode Ma

  3. College of Science, Hebei United University, 063009, Tangshan, Hebei, China

    Baoxiang Liu

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Wei, J., Song, R., Miao, J., Xu, Z. (2013). Evolution Analysis of Online Knowledge Transfer Network. In: Yang, Y., Ma, M., Liu, B. (eds) Information Computing and Applications. ICICA 2013. Communications in Computer and Information Science, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53932-9_45

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  • DOI: https://doi.org/10.1007/978-3-642-53932-9_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53931-2

  • Online ISBN: 978-3-642-53932-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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