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Capturing Designers’ Knowledge Demands in Collaborative Team

  • Conference paper
Cooperative Design, Visualization, and Engineering (CDVE 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4674))

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Abstract

Collaborative team members usually come from diverse disciplines; their demands for knowledge are also different from each other. This paper is mainly concerned with how to capturing designers’ knowledge demands in collaborative team. With the view from workflow, designers’ knowledge demand is modeled from three aspects, members, roles, and tasks’ requirements for knowledge. Based on the model of knowledge demand, some intelligent mining methods are proposed so that designers’ knowledge demand could be derived automatically. With the knowledge demand model, a knowledge supply system could be developed to realize: knowledge within an appropriate domain could be delivered to the proper user among the collaborative team.

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References

  1. Smirnov, A., Pashkin, M., Chilov, N., Levashova, T.: Knowledge logistics in information grid environment. Future Generation Computer Systems 20, 61–79 (2004)

    Article  Google Scholar 

  2. Bollacker, K.D., Lawrence, S., Giles, C.L.: Discovering relevant scientific literature on the Web. IEEE Intelligent Systems 15(2), 42–47 (2000)

    Article  Google Scholar 

  3. Mobasher, B., Cooley, R., Srivastava, J.: Automatic personalization based on web usage mining. Communications of the ACM 43(8), 142–151 (2000)

    Article  Google Scholar 

  4. Konstan, J., Miller, B., Maltz, D.: GroupLens: applying collaborative filtering to usenet news. Communications of the ACM 40(3), 77–87 (1997)

    Article  Google Scholar 

  5. Rucker, J., Siteseer, M.J.: Personalized navigation for the web. Communications of the ACM 40(3), 73–75 (1997)

    Article  Google Scholar 

  6. Sugiyama, K., Hatano, K., Yashikawa, M.: Adaptive web search based on user profile constructed without any effort from users. In: AAMAS 2004, pp. 675–684. IEEE Computer Society Press, Los Alamitos (2004)

    Google Scholar 

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Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R.C.

    Zhen Lu, Jiang Zuhua, Liu Chao & Liang Jun

Authors
  1. Zhen Lu
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  2. Jiang Zuhua
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  3. Liu Chao
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  4. Liang Jun
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Yuhua Luo

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© 2007 Springer-Verlag Berlin Heidelberg

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Lu, Z., Zuhua, J., Chao, L., Jun, L. (2007). Capturing Designers’ Knowledge Demands in Collaborative Team. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2007. Lecture Notes in Computer Science, vol 4674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74780-2_13

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  • DOI: https://doi.org/10.1007/978-3-540-74780-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74779-6

  • Online ISBN: 978-3-540-74780-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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