• DocumentCode
    3705595
  • Title

    Visual analytics of heterogeneous data for criminal event analysis VAST challenge 2015: Grand challenge

  • Author

    Junghoon Chae;Guizhen Wang;Benjamin Ahlbrand;Mahesh Babu Gorantla; Jiawei Zhang; Siqaio Chen; Hanye Xu; Jieqiong Zhao;William Hatton;Abish Malik;Sungahn Ko;David S. Ebert

  • Author_Institution
    Purdue University, USA
  • fYear
    2015
  • Firstpage
    149
  • Lastpage
    150
  • Abstract
    We developed a visual analytics system to analyze the provided heterogeneous 2015 VAST Challenge data. This system utilized several analytic models and visualization techniques. Currently, the underlying data models and clustering techniques have limitations in processing the large volume of data in real time. Therefore, for future work, we will improve the scalability of our system to support real time interactivity and analysis.
  • Keywords
    "Visual analytics","Electronic mail","Trajectory","Tracking","Data visualization","Heating","Data mining"
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on
  • Type

    conf

  • DOI
    10.1109/VAST.2015.7347654
  • Filename
    7347654
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3705595