The mining association rule is an important research field in data mining. The mining association rule usually adopts this model: support, confidence, interestingness. But this model can't measure the correlative degree between the antecedent and the consequent of the rule by ration. So we proposed a new mining model of association rules: support, coincidence, interestingness and analyzed the meaning of coincidence by instance. At last, we used this model in the data about coronary heart disease and obtained a lot of meaningful rules.
基金：
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [J0724003, 60773084, 60603023]; National Research Foundation for the Doctoral Program of Higher Education of ChinaSpecialized Research Fund for the Doctoral Program of Higher Education (SRFDP) [20070151009]
语种：
外文
被引次数：
WOS：
第一作者：
第一作者单位：[1]Dalian Maritime Univ, Dalian, Peoples R China
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推荐引用方式(GB/T 7714)：
Lin Zheng-kui,Yi Wei-guo,Lu Ming-yu,et al.Correlation Research of Association Rules and Application in the Data about Coronary Heart Disease[J].2009 INTERNATIONAL CONFERENCE of SOFT COMPUTING and PATTERN RECOGNITION.2009,143-+.doi:10.1109/SoCPaR.2009.39.
APA：
Lin, Zheng-kui,Yi, Wei-guo,Lu, Ming-yu,Liu, Zhi&Xu, Hao.(2009).Correlation Research of Association Rules and Application in the Data about Coronary Heart Disease.2009 INTERNATIONAL CONFERENCE of SOFT COMPUTING and PATTERN RECOGNITION,,
MLA：
Lin, Zheng-kui,et al."Correlation Research of Association Rules and Application in the Data about Coronary Heart Disease".2009 INTERNATIONAL CONFERENCE of SOFT COMPUTING and PATTERN RECOGNITION .(2009):143-+
