New Generation Computing

, Volume 28, Issue 2, pp 113–120 | Cite as

Building Web Knowledge Flows based on Interactive Computing with Semantics

  • Xiangfeng LuoEmail author
  • Jie Yu
  • Qing Li
  • Fangfang Liu
  • Zheng Xu


Web personalized services alleviate the burden of information overload by providing right information which meets individual user’s needs. How to obtain and represent knowledge needed by users is a key issue. This paper presents Web Knowledge Flow (WKF) to represent the specific knowledge on Web pages and a model of Interactive Computing with Semantics (ICS) to provide a feasible means of generating WKF. Objective WKF (OWKF) and Real-time WKF (RWKF) are firstly proposed to satisfy staged and real-time user interests. Secondly, the generation algorithm of WKF is proposed based on Semantics Link Network. Thirdly, “interactive point” is introduced to detect the moment of user interests change to ensures the dynamics of WKF. Experimental results demonstrate that ICS can effectively capture the change of user interests and the generated WKF can satisfy user requirements accurately.


Web Knowledge Flow Interactive Computing with Semantics Semantics Link Network User Interest 


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  1. 1.
    Nissen, M. E., “An Extended Model of Knowledge Flow Dynamics,” Communications of the Association for Information Systems, pp. 251-266, 2002.Google Scholar
  2. 2.
    Zhuge, H., Guo, W., Li, X., Ding, L., “Knowledge Energy in Knowledge Flow Networks,” in Pro. Int. Conf. Semantics, Knowledge and Grid, 2005.Google Scholar
  3. 3.
    Zhuge, H., “Autonomous semantic link network model for the Knowledge Grid,” Concurrency and Computation: Practice and Experience, 7, 19, pp.1065-1085, 2007.CrossRefGoogle Scholar
  4. 4.
    Luo, X. F., N. F., “Semantic Representation of Scientific Documents for the e-Science Knowledge Grid,” Concurrency and Computation: Practice and Experience, 20, 7, pp. 839-862, 2008.Google Scholar
  5. 5.
    Wegner, P., “Interactive foundations of computing,” Theoretical Computer Science, 192, 2, pp. 839-862, 1998.CrossRefMathSciNetGoogle Scholar
  6. 6.
    Pazzani, M., et al., “Learning and Revising User Profiles: The Identification of Interesting Web Sites,” in Machine Learning, pp. 313-331, 1997.Google Scholar
  7. 7.
    Luo, X. F., et al., “Discovery of Associated Topics for the Intelligent Browsing,” in Pro. 1st IEEE Int. Conf. Ubi-Media Computing and Workshops, pp.119-125, 2008.Google Scholar
  8. 8.
    Raghavan, V. V., et al., “A critical analysis of vector space model for information retrieval,” in Journal of the American Society for Information Science, 37, 5, pp. 279-287, 1986.MathSciNetGoogle Scholar

Copyright information

© Ohmsha and Springer Japan jointly hold copyright of the journal. 2010

Authors and Affiliations

  • Xiangfeng Luo
    • 1
    Email author
  • Jie Yu
    • 1
  • Qing Li
    • 1
    • 2
  • Fangfang Liu
    • 1
  • Zheng Xu
    • 1
  1. 1.School of Computer Engineering and ScienceShanghai UniversityShanghaiChina
  2. 2.City University of Hong KongHong KongChina

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