基于艾宾浩斯遗忘曲线的零售商品模糊关联分析
针对消费者对商品的偏好存在时序变化特征,而传统关联规则方法未考虑时间因素的影响,且对海量数据集进行关联挖掘时存在效率低下的问题,提出了基于艾宾浩斯遗忘曲线的模糊关联规则算法。该方法通过FCM聚类算法对商品进行聚类,并用艾宾浩斯遗忘曲线来修正聚类的距离度量方法,从而得到商品类及各类的代表点商品;然后将各代表点商品作为属性,消费记录小票作为样本,利用模糊关联规则算法得到代表点商品间的规则;最后将某大型超市一个月的销售记录作为关联规则的事务数据来挖掘潜在规律,结果显示所提算法先对商品模糊关联分析,与传统直接对商品进行关联分析相比,该算法可以显著提高关联挖掘的效率和规则的正确率。...
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| Published in | 计算机应用研究 Vol. 35; no. 2; pp. 462 - 465 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
大连海事大学交通运输管理学院,辽宁大连,116026
2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2018.02.030 |
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| Abstract | 针对消费者对商品的偏好存在时序变化特征,而传统关联规则方法未考虑时间因素的影响,且对海量数据集进行关联挖掘时存在效率低下的问题,提出了基于艾宾浩斯遗忘曲线的模糊关联规则算法。该方法通过FCM聚类算法对商品进行聚类,并用艾宾浩斯遗忘曲线来修正聚类的距离度量方法,从而得到商品类及各类的代表点商品;然后将各代表点商品作为属性,消费记录小票作为样本,利用模糊关联规则算法得到代表点商品间的规则;最后将某大型超市一个月的销售记录作为关联规则的事务数据来挖掘潜在规律,结果显示所提算法先对商品模糊关联分析,与传统直接对商品进行关联分析相比,该算法可以显著提高关联挖掘的效率和规则的正确率。 |
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| AbstractList | TP391%C931.9; 针对消费者对商品的偏好存在时序变化特征,而传统关联规则方法未考虑时间因素的影响,且对海量数据集进行关联挖掘时存在效率低下的问题,提出了基于艾宾浩斯遗忘曲线的模糊关联规则算法.该方法通过FCM聚类算法对商品进行聚类,并用艾宾浩斯遗忘曲线来修正聚类的距离度量方法,从而得到商品类及各类的代表点商品;然后将各代表点商品作为属性,消费记录小票作为样本,利用模糊关联规则算法得到代表点商品间的规则;最后将某大型超市一个月的销售记录作为关联规则的事务数据来挖掘潜在规律,结果显示所提算法先对商品模糊关联分析,与传统直接对商品进行关联分析相比,该算法可以显著提高关联挖掘的效率和规则的正确率. 针对消费者对商品的偏好存在时序变化特征,而传统关联规则方法未考虑时间因素的影响,且对海量数据集进行关联挖掘时存在效率低下的问题,提出了基于艾宾浩斯遗忘曲线的模糊关联规则算法。该方法通过FCM聚类算法对商品进行聚类,并用艾宾浩斯遗忘曲线来修正聚类的距离度量方法,从而得到商品类及各类的代表点商品;然后将各代表点商品作为属性,消费记录小票作为样本,利用模糊关联规则算法得到代表点商品间的规则;最后将某大型超市一个月的销售记录作为关联规则的事务数据来挖掘潜在规律,结果显示所提算法先对商品模糊关联分析,与传统直接对商品进行关联分析相比,该算法可以显著提高关联挖掘的效率和规则的正确率。 |
| Abstract_FL | Consumers' preference for goods has the characteristics of sequential variation.However,the traditional association rule method has not considered the influence of time factor,and there is the problem of low efficiency in the association mining of massive data sets.Therefore,this paper proposed a fuzzy association rule algorithm based on Ebbinghaus forgetting curve.First of all,this algorithm employed the FCM clustering algorithm to cluster the goods,and introduced the Ebbinghaus forgetting curve for revising the clustering distance metrics,so that to get the goods clusters and all kinds of representative point goods.And then,it used each representative point as the attribute,and used the shopping receipt as the sample,and utilized fuzzy association rules algorithm to get the rules of the representative points.Finally,this paper used the sales records of a large supermarket as the transaction data of the association rules to mine the potential rules.The results show that the proposed algorithm can not only consider the time factor,but also apparently improve the efficiency and accuracy of association mining. |
| Author | 李桃迎;张鑫;陈燕 |
| AuthorAffiliation | 大连海事大学交通运输管理学院,辽宁大连116026 |
| AuthorAffiliation_xml | – name: 大连海事大学交通运输管理学院,辽宁大连,116026 |
| Author_FL | Chen Yan Li Taoying Zhang Xin |
| Author_FL_xml | – sequence: 1 fullname: Li Taoying – sequence: 2 fullname: Zhang Xin – sequence: 3 fullname: Chen Yan |
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| Keywords | 模糊关联规则 association rules fuzzy association rules 艾宾浩斯遗忘曲线 cluster analysis 聚类分析 Ebbinghaus forgetting curve 关联规则 |
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| Notes | 51-1196/TP Ebbinghaus forgetting curve; cluster analysis; association rules; fuzzy association rules Consumers＇ preference for goods has the characteristics of sequential variation. However, the traditional associa- tion rule method has not considered the influence of time factor, and there is the problem of low efficiency in the association mining of massive data sets. Therefore, this paper proposed a fuzzy association rule algorithm based on Ebbinghaus forgetting curve. First of all, this algorithm employed the FCM clustering algorithm to cluster the goods, and introduced the Ebbinghaus forgetting curve for revising the clustering distance metrics, so that to get the goods clusters and all kinds of representative point goods. And then, it used each representative point as the attribute, and used the shopping receipt as the sample, and utilized fuzzy association rules algorithm to get the rules of the representative points. Finally, this paper used the sales records of a large supermarket as the transaction da |
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| Title | 基于艾宾浩斯遗忘曲线的零售商品模糊关联分析 |
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