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改进购物篮分析的关联规则挖掘算法
Association Rule Mining Algorithm on Improved Market Basket Analysis
【摘要】 基于改进传统购物篮分析的关联规则挖掘是在数据处理时引入兴趣度加权的思想,将所有交易中同一类商品的交易量进行归一化处理,根据用户领域知识的要求,计算该类商品的兴趣度加权阈值,从而改进传统的购物篮分析,使所挖掘出的关联规则符合实际,同时减少关联规则挖掘的工作量,提高规则挖掘的效率和准确性.
【Abstract】 Association rules mining based on improved traditional market basket analysis is that we introduce the idea of interest-weighed into data processing,normalize the amount of the same kind of commodity purchased by customers in all transactions.According to the demand of users’ domain knowledge,we can calculate the interest-weighed threshold,then improve the traditional market basket analysis,association rules are mined much more practical,the workload of(association) rules mining has been reduced,the efficiency and veracity of association rules mining are improved.
【Key words】 association rules; apriori algorithm; frequent itemsets; data mining;
- 【文献出处】 重庆大学学报(自然科学版) ,Journal of Chongqing University(Natural Science Edition) , 编辑部邮箱 ,2006年04期
- 【分类号】TP311.13
- 【被引频次】44
- 【下载频次】1011