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Improvement of Thinking Theme Construction Algorithm Based on Analysis Question Clustering

In: Liss 2013

Author

Listed:
  • Xuedong Gao

    (University of Science and Technology Beijing)

  • Lei Zou

    (University of Science and Technology Beijing)

  • Zengju Li

    (Bank Card Test Center)

Abstract

To achieve intelligent data analysis, thinking theme construction technology is proposed. While current thinking theme construction algorithm is based on hierarchical clustering, the efficiency of which is far from acceptable with the increasing of number of analysis questions. This paper improves the efficiency of the algorithm based on density clustering. The experimental results with five datasets from complex network and one commercial theme data show that both of the clustering effectiveness and efficiency are improved.

Suggested Citation

  • Xuedong Gao & Lei Zou & Zengju Li, 2015. "Improvement of Thinking Theme Construction Algorithm Based on Analysis Question Clustering," Springer Books, in: Runtong Zhang & Zhenji Zhang & Kecheng Liu & Juliang Zhang (ed.), Liss 2013, pages 579-583, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-40660-7_85
    DOI: 10.1007/978-3-642-40660-7_85
    as

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