摘要
在处理战略绩效KPI关联规则挖掘的问题时,由于FP-Growth不能根据业务的需要简化计算过程,从而产生了许多冗余计算,影响了算法的效率。因此,提出了一种基于FP-Growth的战略绩效关联分析算法。通过采用基于规则的约束方法对FP-Growth算法进行改进。一方面,在挖掘的过程中添加剪枝操作,提高频繁项集的挖掘效率;另一方面,在关联规则产生过程中,添加规则约束,生成符合业务要求的关联规则,从而减少了冗余计算,提高了算法的效率。最后,以"某高校科研服务质量指标"为例,验证了该算法的可行性。
When dealing with the issues of KPI association rule mining on strategic performance,FP-Growth can＇t simplify the computing process according to requirements of business,and caused lots of redundant computing which effected the efficiency of the algorithm,So a FP-Growth based association analysis algorithm of strategic performance is proposed.By the constraint method based on rules,the FP-Growth algorithm is advanced.On the one hand,the efficiency of frequent item set mining is improved by adding clipping operation in the process of mining.On the other hand,association rules based on business are generated by adding constraints based on rules in the process of association rule generating process,therefore,redundant computing is reduced and efficiency of the algorithm is improved.At last,a case of ＂service quality indicators for research in a university＂ is presented to verify the feasibility of the algorithm.
出处
《微计算机应用》
2011年第2期1-8,共8页
Microcomputer Applications
基金
上海市教委"上海大学SAP不动产项目(20080101)"资助
