Please use this identifier to cite or link to this item: https://doi.org/10.1145/2339530.2339774
Title: AssocExplorer: An association rule visualization system for exploratory data analysis
Authors: Liu, G. 
Suchitra, A.
Zhang, H.
Feng, M.
Ng, S.-K.
Wong, L. 
Keywords: exploratory data analysis
rule exploration
rule visualization
Issue Date: 2012
Citation: Liu, G., Suchitra, A., Zhang, H., Feng, M., Ng, S.-K., Wong, L. (2012). AssocExplorer: An association rule visualization system for exploratory data analysis. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining : 1536-1539. ScholarBank@NUS Repository. https://doi.org/10.1145/2339530.2339774
Abstract: We present a system called AssocExplorer to support exploratory data analysis via association rule visualization and exploration. AssocExplorer is designed by following the visual information-seeking mantra: overview first, zoom and filter, then details on demand. It effectively uses coloring to deliver information so that users can easily detect things that are interesting to them. If users find a rule interesting, they can explore related rules for further analysis, which allows users to find interesting phenomenon that are difficult to detect when rules are examined separately. Our system also allows users to compare rules and inspect rules with similar item composition but different statistics so that the key factors that contribute to the difference can be isolated. © 2012 ACM.
Source Title: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
URI: http://scholarbank.nus.edu.sg/handle/10635/40310
ISBN: 9781450314626
DOI: 10.1145/2339530.2339774
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