基于数据挖掘建立动态人事管理决策系统

The Establishment of an Recent Mamagement and Decision System of Personnel Based on Data Mining

运用关联规则发现方法对人事信息库进行数据挖掘,生成了对当前数据库有效的关联规则,为高校管理决策提供科学依据。但数据库的更新操作经常发生,原来有效的部分规则可能在更新后的数据库中会成为无效,原无效的部分规则也同样有可能会成为有效。文章提出了EPUA算法,有效解决了数据更新后关联规则的更新问题,对FUP2算法进行了补充和改进。

We use the method of discovering association rules to mine knowledge in personnel databases,the generated rules are valid in the current database,which provide a scientific basis for college management and decision making.But the database is often updated,some original rules may become invalid in the updated database,and similarly,some origi-nal invalid rules may become valid.In this thesis,we propose EFUP algorithms ,and find an effective solution to the problem of maintaining the association rule,after the database is updated.We improve FUP2algorithms.