• DocumentCode
    554059
  • Title

    A visualization system for web retrieved credit information

  • Author

    Lirong Xiong ; Mengjun Wang ; Jing Fan

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China
  • Volume
    2
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    728
  • Lastpage
    733
  • Abstract
    Information retrieved with traditional method results in linear lists which lack of effective filtration, organization, and aggregation. How to organize and visualize the retrieved information result set effectively and how to provide users with the effective interaction becomes increasingly important. Based on the Information Visualization Model, this paper studies the key technologies. The data clustering methods and suitable display technologies are analyzed. Then, this paper proposes an information visualization model for credit domain, and describes a visualization system for web retrieved credit information. The system can crawl credit related web pages, and after analyzing the characteristics of credit information, SOM-based clustering method is applied to well organize the web pages, and visualization technology is used to present the documents information globally and locally. In this way, user can understand credit information better. At last, examples of visual display for credit information are shown in this paper.
  • Keywords
    Internet; data visualisation; information retrieval; pattern clustering; self-organising feature maps; SOM-based clustering; Web retrieved credit information; credit related Web pages; data clustering; information visualization model; visual display; Clustering algorithms; Clustering methods; Data mining; Data visualization; Visualization; Web pages; SOM; credit; information visualization; self-organization map; visualization system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2011 Seventh International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4244-9950-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2011.6022206
  • Filename
    6022206