基于改进FP_Growth算法在中药提取信息中研究  

Research of traditional Chinese medicine data mining based on improved FP-Growth algorithm

作　　者：马健[1] 董辉[1] 

机构地区：[1]亳州职业技术学院信息工程系,安徽亳州236800

出　　处：《楚雄师范学院学报》2011年第9期17-23,共7页Journal of Chuxiong Normal University

摘　　要：中药提取在中药生产中占有十分重要地位,企业在生产中药过程中,生产过程数据和质量数据存在一定的问题。数据挖掘技术的出现及利用k-means聚类算法和改进的FP_Growth算法对中药生产过程数据进行分析,既能为企业提高生产效率,降低成本,又保证产品的质量。因此对中药提取信息数据挖掘不仅是有必要的,更具有实际意义。Chinese medicine extraction plays a very important role in the production of tradition- al Chinese medicine. There are some problems in the process data and quality data from enterprises＇ Chinese medicine production. The emergence of data mining techniques and the use of k - means clustering algorithm and improved FP - Growth algorithm to analyze the data of traditional Chinese medicine production process, both improved enterprises productivity and reduced costs, and as well as ensure product quality. Therefore, data mining of Chinese medicine extraction is necessary and practical.

关 键 词：数据挖掘 关联规则 中药提取 FP—Growth算法 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]