Construction and evaluation of structured association map for visual exploration of association rules

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• 作者：Jun Woo Kim ^{kjunwoo@dau.ac.kr}
• 关键词：Visual exploration ; Data mining ; Association rule mining ; Hierarchical clustering ; Structured association map ; Health examination
• 刊名：Expert Systems with Applications
• 出版年：2017
• 出版时间：15 May 2017
• 年：2017
• 卷：74
• 期：Complete
• 页码：70-81
• 全文大小：2150 K
• 卷排序：74

文摘

SAM provides enhanced visual aids for representing the many-to-many association rules in large transaction data. The performance of SAM can be numerically evaluated by using S2C measure. SAM enables users to conveniently identify the interesting areas that might contain interesting association rules. SAMs with higher S2C values are more useful for visual exploration of association rules.