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量化中药功效相似度是方剂功效规约中一个基本而重要的问题。采用数据挖掘技术对该问题进行了探讨,即从现有的药物记载功效中挖掘出功效之间的相似关系。该方法首先通过关联规则算法获得强双向关联功效对,以去除相关程度较小的功效对,然后采用SimRank迭代算法求取功效之间的相似。基于这样的思路,获得了比较合理与客观的功效相似度。与人工方法计算功效相似度相比,既大大降低了工作量,又减少了主观性。为方剂功效规约研究打下了基础。
Quantifying the similarity of TCM efficacy is a basic and important issue in the prescription of prescription efficacy. The data mining technology is used to explore the issue, that is, the similarities between the efficiencies can be found out from the existing medical records. The method first obtains a strong bidirectional correlation effect pair through the association rule algorithm to remove the less relevant pairs, and then uses the SimRank iterative algorithm to obtain the similarities between the efficiencies. Based on this idea, we obtain a more reasonable and objective similarity of efficacy. Compared with the similarity of artificial method of calculating efficiency, it not only greatly reduces the workload but also reduces the subjectivity. For prescription efficacy protocol study laid the foundation.