• DocumentCode
    3078357
  • Title

    A Tool for Visualizing Topic Evolution in Large Text Collections

  • Author

    Feipeng Sun ; Yanyan Li ; Zhiqiang Zhang

  • Author_Institution
    R&D Center for Knowledge Eng., Beijing Normal Univ., Beijing, China
  • fYear
    2013
  • fDate
    15-18 July 2013
  • Firstpage
    53
  • Lastpage
    54
  • Abstract
    Topic evolution in text data has become a flourishing frontier in the text mining community. Yet with the increasing number of texts, it is important and challenging to understand how topics evolve. In this paper, we introduce a tool to analyze various evolution patterns that emerge from multiple texts based on combination of topic modeling and visualization techniques. By mining topic hierarchical relationship and evolutionary trend, the tool provides three visualization views along with interactive functionality that enables users to understand the topic evolution in a flexible and easily way. Experiment on real dataset has shown that the developed tool is effective to visualizing meaningful topic evolution in large text collections.
  • Keywords
    data mining; data visualisation; text analysis; evolution patterns; interactive functionality; large text collection; text data; text mining community; topic evolution visualisation; topic modeling; topic visualisation; visualization techniques; Conferences; Data models; Data visualization; Educational institutions; Market research; Resource management; Visualization; Hierarchical Latent Dirichlet Allocation; Topic evolution; interaction design; visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Learning Technologies (ICALT), 2013 IEEE 13th International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/ICALT.2013.21
  • Filename
    6601864