购物篮分析 meaning in English
market basket anlysis
Examples
- Market basket analysis
购物篮分析法： - The third part talks about the analysis and design of the business intelligence module which is a part of zhen xiang project , then explores the application of data mining to provide market basket analysis , customer classification analysis and other intelligent analyses . we research on how to provide intelligent analysis based on data mining for the enterprise in the e - commerce system
本文对振湘项目二期工程的商业智能分析子系统进行了分析和设计，尝试应用数据挖掘来完成购物篮分析、客户细分等分析功能，并且对在电子商务系统中结合企业需求提供基于数据挖掘的智能分析服务进行了有意义的研究探索。 - ( 2 ) traditional marked - basket analysis has been improved , since it only cares for that the customer have bought something or not , ignores the quantity of those bought , there are some more limitations in practical application . in the paper , i am concerned about both cases , then introduce the idea of interest - weighted to marked - basket analysis , put forward the algorithm how to acquire the interest - weighted threshold , therefore , the association rules mining by interest - weighted on quantitative extended concept lattice is more practical
改进了传统的购物篮分析，由于传统的购物篮分析只关心顾客是否购买商品，忽略其购买的数量，因而在实际应用中，有很大的局限性，在本文中，不仅要关心顾客是否购买商品，而且考虑顾客购买的数量，在传统的购物篮分析中，引入兴趣度加权思想，并提出了如何获取兴趣度加权阈值的方法，因此在改进了传统的购物篮分析基础上，基于量化概念格所挖掘出的关联规则有更贴近于实际和应用价值。 - This tutorial walks you through scenarios for targeted mailing , forecasting , market basket analysis , and sequence clustering , to demonstrate how to use the data mining algorithms , mining model viewers , and data mining tools that are included in microsoft sql server 2005 analysis services ssas
本教程将指导您演练目标邮件、预测、购物篮分析以及顺序分析和聚类分析等方案，阐释如何使用microsoft sql server 2005 analysis services ( ssas )提供的数据挖掘算法、挖掘模型查看器以及数据挖掘工具。 - Association rules mining , as the most important subject in data mining , reveals the corelations between itemsets and therefore can be widely applied to many fields such as market basket analysis , corelation analysis , classification , web - customised service , etc . since 1993 when r . agrawal , r . srikant firstly proposed the concept of association rules , a lot of algorithms have come up in mining of association rules
关联规则揭示项集间有趣的相联关系，可广泛应用于购物篮分析、相关分析、分类、网络个性化服务等领域，是数据挖掘的重要研究课题。自1993年r . agrawal ， r . srikant首次提出该问题以来，已出现了许多关联规则挖掘算法。