计算机科学 ›› 2013, Vol. 40 ›› Issue (3): 259-262.

• 人工智能 • 上一篇    下一篇

基于时序和兴趣度约束的加权关联规则挖掘算法研究

杨泽民   

  1. (山西大同大学数学与计算机科学学院 大同037009)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Study of Weighted Association Rules Mining Algorithms Based on Timing and Interest Degrees Constraints

  • Online:2018-11-16 Published:2018-11-16

摘要: 为了解决关联规则挖掘算法中频繁集信息挖掘不完善和时序周期对事务集频繁项挖掘的影响问题,提出了一种基于时序和兴趣度约束的加权关系规则挖掘算法。该算法首先利用时序滑动函数对时序事务集进行发生概率估算和权值赋值,依据兴趣度约束函数和剪枝定理进行事务集化简,然后根据支持度和寿支持期望进行加权频繁事务集抽取,最后依据置信度进行加权关联规则导出。实验结果证明,该算法能够快速有效地挖掘出符合用户兴趣度的关联规则。

关键词: 加权关联规则,时序挖掘,支持度,兴趣度约束,频繁事务集

Abstract: In order to solve the problems that the frequent set information mining is not perfect in the association rule mining algorithm and the timing cycle influences mining of transaction set frequent item, a weighted association rules mining algorithms based on the timing and interest degrees constraints was proposed. This algorithm firstly uses sequcntial sliding function of the timing affairs set for probability estimation and weight assignment, then sets simplificalion according to the interests of the constraint function and pruning theorem transaction, makes a weighted frectuent transaction set extraction according to the degree of support and support expectations, lastly derives weighted associalion rules based on the confidence.The experimental results show that the algorithm can meet the users requirement in mining association rules quickly and effectively.

Key words: Weighted association rul}s,Liming mining,Support,Interest degrees constraints,Frequcnt affairs set

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