InterVisAR: An Interactive Visualization for Association Rule Search

• Type of Material: Article
• Authors: Chih-Wen Cheng, Georgia Institute of Technology; Ying Sha, Georgia Institute of Technology; Dongmei Wang, Emory University
• Language: English
• Date: 2016-01-01
• Publisher: Association for Computing Machinery
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2016 ACM, Inc.
• Final Published Version (URL): http://dx.doi.org/10.1145/2975167.2975185
• Title of Journal or Parent Work: BCB '16: Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
• Volume: 2016
• Start Page: 175
• End Page: 184
• Grant/Funding Information: This research has been supported by grants from NIH (U54CA119338, 1RC2CA148265, and R01CA163256), Georgia Cancer Coalition Award to Prof. MD Wang, Hewlett Packard, and Microsoft Research.
• Keywords: Medical Informatics; visualization techniques; Life Sciences & Biomedicine; methodologies; Association rules; Computer Science; Technology; knowledge visualization; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Science & Technology
• Research Categories: Engineering, Biomedical; Biology, Bioinformatics; Computer Science

Abstract

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 comparing with table-based rule search.