摘要
将频繁项集挖掘算法中的FP-Growth算法应用到毕业生信息管理系统中,算法采用FP树对事务数据集进行压缩存储,然后再利用FP树得到所有的频繁项集.该系统可从大量的毕业生信息出发,找出就业信息与教育信息之间的关系,从而为决策者提供指导或数据支持.
The FP-Growth algorithm of frequent itemsets mining algorithm was applied to the graduate information management system. The FP tree of transaction data set to compress and storaged in this algorithm,and then re-uses FP tree to get all the frequent itemsets. The system could find out the relationship between the employment information and education information,based on a large number of graduates information,so as to provide guidance or data support.
出处
《郑州轻工业学院学报（自然科学版）》
CAS
2013年第5期59-61,共3页
Journal of Zhengzhou University of Light Industry:Natural Science
