摘要
为了实现在海量数据中的审计线索的快速发现,通过数据挖掘FMA算法对被审数据和审计专家经验库进行关联规则快速提取;再利用自组织神经网络改良CLARANS算法对审计专家经验库抽取的规则划分出相似规则群;然后通过对被审单位关联规则集合和专家经验的相似规则群进行相对强弱、趋近率和价值率的比较,最终得到审计线索集合。
In order to achieve the audit trail of the massive data quickly found through data mining FMA algorithms to quickly extract trial data and audit expertise library association rules;re-use of self-organizing neural network improved CLARANS algorithm to extract audit expertise library divide a similar rule base rules;then by trial set of association rules and expert experience similar rules group relative strength, the approach value and the different rate of comparing the resulting set of audit trail.
出处
《计算机工程与应用》
CSCD
2014年第22期154-157,179,共5页
Computer Engineering and Applications
基金
江苏省公共工程审计重点实验室开放课题(No.20201201213)
江苏省审计信息工程重点实验室开放课题(No.AIE201205)
国家自然科学基金(No.70971067
No.71271117)
