• DocumentCode
    245430
  • Title

    A Visualizer for High Utility Itemset Mining

  • Author

    Wei Song ; Mingyuan Liu

  • Author_Institution
    Coll. of Comput., North China Univ. of Technol., Beijing, China
  • fYear
    2014
  • fDate
    19-21 Dec. 2014
  • Firstpage
    244
  • Lastpage
    248
  • Abstract
    Mining high utility item sets is one of the most important research issues in data mining owing to its ability to consider nonbinary frequency values of items in transactions and different profit values for each item. Although several studies have been carried out, current methods present the mined results in the form of textual lists for users, which degrades the understand ability of the discovered high utility item sets. To address this issue, we propose an effective visualizer, namely HUIViz (High Utility Item set Visualizer), for displaying the mined high utility item sets. HUIViz provides users with an overview as well as details about the item sets. Moreover, the visualizer is also equipped with several interactive features for effective visualization of high utility item sets. More importantly, as the discovery process of high utility item set is composed of two phases, HUIViz shows results of two stages in two views of one screen. Thus, the changes from the temporal results stage to the final results stage can be displayed clearly. The evaluation conducted on both synthetic and real datasets show that the proposed visualizer is effective.
  • Keywords
    data mining; data visualisation; HUIViz visualizer; data mining; data visualization; frequency values; high utility itemset mining; textual list; Association rules; Color; Data visualization; Image color analysis; Itemsets; Visualization; data mining; high utility itemset; interaction; visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-7980-6
  • Type

    conf

  • DOI
    10.1109/CSE.2014.75
  • Filename
    7023586