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基于中药专利数据集的关联规则发现算法 被引量：2

Discovering Rules Based on Traditional Chinese Medicine Patent Dataset
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摘要 指出关联规则在中药数据分析中的难点,据此提出了一种改进的Apriori算法——Apriori+算法;最后,以治疗感冒的中药专利数据集为测试数据,进一步验证算法的有效性和实用性。结果表明,此算法能够有效地从治疗感冒的专利数据库中发现布尔型与数值型关联规则,为开发新的感冒中药提供配伍依据。 The algorithm of discovering association rules is applied to the TCM patent database so as to discover the pharmaceutical principles of basic elements and supply the decision making information to explore new medicine. This paper pointed out the difficulties in applying association rule to analyze TCM data, based on which, Apriori ＋, an improved Apriori algorithm was introduced. Finally, through tests on the data set of curing cold, effectivity and practicability of the algorithm was further proved. The results show that the algorithm can effectively discovery the boolean and quantitative association rules from the TCM patent database and provide supports for the pharmaceutical rule of TCM on exploring new cold Chinese medicine.
作者 钱增瑾 辛燕 鞠时光
机构地区 南京理工大学研究生院 江苏大学计算机学院
出处 《计算机应用研究》 CSCD 北大核心 2007年第7期61-63,共3页 Application Research of Computers
基金 国家"863"计划资助项目(2002AA412020) 校青年基金资助项目(1241170006)
关键词 数据挖掘 数据顸处理 关联规则 中药配伍规则 data mining data pretreatment association rules pharmaceutical rule of TCM
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献8

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共引文献18

同被引文献18

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引证文献2

二级引证文献14

计算机应用研究
2007年 第7期

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