Mining Large-Scale News Video Database Via Knowledge Visualization

  • Hangzai Luo
  • Jianping Fan
  • Shin’ichi Satoh
  • Xiangyang Xue
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4781)


In this paper, a novel framework is proposed to enable intuitive mining and exploration of large-scale video news databases via knowledge visualization. Our framework focuses on two difficult problems: (1) how to extract the most useful knowledge from the large amount of common, uninteresting knowledge of large-scale video news databases, and (2) how to present the knowledge to the users intuitively. To resolve the two problems, the interactive database exploration procedure is modeled at first. Then, optimal visualization scheme and knowledge extraction algorithm are derived from the model. To support the knowledge extraction and visualization, a statistical video analysis algorithm is proposed to extract the semantics from the video reports.


Multimedia Mining Knowledge Visualization 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hangzai Luo
    • 1
  • Jianping Fan
    • 2
  • Shin’ichi Satoh
    • 3
  • Xiangyang Xue
    • 4
  1. 1.Software Engineering Institute, East China Normal University, ShanghaiChina
  2. 2.Department of Computer Science, UNC-Charlotte, CharlotteUSA
  3. 3.National Institute of Informatics, TokyoJapan
  4. 4.Department of Computer Science, Fudan University, ShanghaiChina

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