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InterVisAR
Author(s) -
ChihWen Cheng,
Ying Sha,
May D. Wang
Publication year - 2016
Publication title -
pubmed central
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2975167.2975185
Subject(s) - association rule learning , visualization , computer science , data mining , table (database) , data visualization , property (philosophy) , information retrieval , information visualization , philosophy , epistemology
Association rule mining has been utilized extensively in many areas because it has the ability to discover relationships among variables in large databases. However, one main drawback of association rule mining is that it attempts to generate a large number of rules and does not guarantee that the rules are meaningful in the real world. Many visualization techniques have been proposed for association rules. These techniques were designed to provide a global overview of all rules so as to identify the most meaningful rules. However, using these visualization techniques to search for specific rules becomes challenging especially when the volume of rules is extremely large. In this study, we have developed an interactive association rule visualization technique, called InterVisAR, specifically designed for effective rule search. We conducted a user study with 24 participants, and the results demonstrated that InterVisAR provides an efficient and accurate visualization solution. We also verified that InterVisAR satisfies a non-factorial property that should be guaranteed in performing rule search. All participants also expressed high preference towards InterVisAR as it provides a more comfortable and pleasing visualization in association rule search.

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