• DocumentCode
    125402
  • Title

    A New Type of Web Graph for Personalized Visualization

  • Author

    Saleheen, Shibli ; Wei Lai

  • Author_Institution
    Fac. of Inf. & Communicaction Technol., Swinburne Univ. of Technol., Hawthorn, VIC, Australia
  • fYear
    2014
  • fDate
    4-7 March 2014
  • Firstpage
    238
  • Lastpage
    242
  • Abstract
    Over the past few years, research on web information visualization is focusing on how to present the web information to end users effectively and efficiently. Nevertheless, with increasing size of the information in the web-space, it has become very difficult to visualize information and the inherent relationships among the information. Because of web graphs being messy and large, end users need to allow extra effort to mine interested information from those. Existing web graphs produce relationships among nodes (URLs) based on structural linkage information. As a result, by producing similar visualization to different end users, this approach lacks effectiveness considering diversity of users´ need. In our work, we encounter this issue of personalization in visualization of web graph. We propose a different web graph which capitalizes on user interests to develop relationships among nodes of the web graph. Examples show that this web graph can represent web information to the end user for more effective and effortless information search.
  • Keywords
    Internet; data visualisation; graph theory; URLs; Web graph visualization; Web information visualization; Web-space; information search; personalized visualization; structural linkage information; Couplings; Data visualization; Educational institutions; Image edge detection; Joining processes; Visualization; Web pages; Graphs and Networks; Hypertext/Hypermedia; Information Search and Retrieval; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visualization Symposium (PacificVis), 2014 IEEE Pacific
  • Conference_Location
    Yokohama
  • Type

    conf

  • DOI
    10.1109/PacificVis.2014.19
  • Filename
    6787173