数据挖掘关联规则.ppt

5/25/2017 Data Mining: Concepts and Techniques 1 Chapter 4: Mining Frequent Patterns, Association and Correlations ? Basic concepts and a road map ? Scalable frequent itemset mining methods ? Mining various kinds of association rules ? Constraint-based association mining ? From association to correlation analysis ? Mining colossal patterns ? Summary 5/25/2017 Data Mining: Concepts and Techniques 2 What Is Frequent Pattern Analysis? ? Frequent pattern : a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set ? First proposed by Agrawal, Imielinski , and Swami [AIS93] in the context of frequent itemsets and association rule mining ? Motivation: Finding inherent regularities in data ? What products were often purchased together? — Beer and diapers?! ? What are the subsequent purchases after buying a PC? ? What kinds of DNA are sensitive to this new drug? ? Can we automatically classify web documents? ? Applications ? Basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. 5/25/2017 Data Mining: Concepts and Techniques 3关联规则挖掘?关联规则挖掘的典型案例: 购物篮问题?在商场中拥有大量的商品(项目),如:牛奶、面包等,客户将所购买的商品放入到自己的购物篮中。?通过发现顾客放入购物篮中的不同商品之间的联系,分析顾客的购买****惯?哪些物品经常被顾客购买? ?同一次购买中,哪些商品经常会被一起购买? ?一般用户的购买过程中是否存在一定的购买时间序列? ?具体应用:利润最大化?商品货架设计:更加适合客户的购物路径?货存安排:实现超市的零库存管理?用户分类:提供个性化的服务 5/25/2017 Data Mining: Concepts and Techniques 4关联规则挖掘简单的说, 关联规则挖掘就是发现大量数据中项集之间有趣的关联在交易数据、关系数据或其他信息载体中,查找存在于项目集合或对象集合之间的频繁模式、关联、相关性、或因果结构。应用购物篮分析、交叉销售、产品目录设计、聚集、分类等两种策略: 1。商品放近, 增加销量 2。商品放远, 增加其他商品的销量 5/25/2017 Data Mining: Concepts and Techniques 5 Why Is Freq. Pattern Mining Important? ? Freq. pattern: An intrinsic and important property of datasets ? Foundation for many essential data mining tasks ? Association, correlation, and causality analysis ? Sequential, structural (., sub-graph) patterns ? Pattern analysis in spatiotemporal, multimedia, time- series, and stream data ? Classificat