改进的序列模式挖掘在医院转诊中的应用  

Application of Improved Sequential Pattern mining in Hospital Referral

作　　者：陶惠[1] 蒋凡[1] 

机构地区：[1]中国科学技术大学计算机科学与技术学院,合肥230027

出　　处：《计算机系统应用》2015年第10期253-258,共6页Computer Systems & Applications

基　　金：高等学校博士学科点专项科研基金新教师类资助课题(20113402120026);安徽省自然科学基金(1208085QF112);安徽省高等学校优秀青年人才基金(2012SQRL001ZD);中央高校基本科研业务费专项资金(WK2101020004;WK0110000007)

摘　　要：为了研究患者在不同医院间的转诊行为模式,可以使用序列模式挖掘算法.类Apriori算法是序列模式挖掘中的常用算法,但该算法存在一些不足之处,如产生候选序列的数目较多、需要频繁扫描数据库.针对类Apriori算法存在的不足,本文提出了相应的改进措施,采用新的剪枝策略并减少不必要的数据库扫描操作.实验证明,改进后的算法能更高效地挖掘频繁转诊序列.In order to analyze the patients＇ referral behavior pattern among different hospitals, the sequential pattern mining algorithm can be applied. Apriori-like algorithm is the classical algorithm in the sequential pattern mining, but there are some deficiencies, such as generating too many candidate sequences and scanning the database too often. To solve such problems, this paper has proposed some measures for improvement, including using a new pruning strategy and reducing the unnecessary scans of the database. The experiments prove that the improved algorithm performs more efficiently in the frequent referral sequence mining.

关 键 词：序列模式挖掘 类Apriori算法 剪枝 医院转诊序列 转诊行为分析 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]