一种改进的关联规则挖掘方法  

One Improved Data Mining Method of Association Rules

作　　者：魏本昌[1] 刘辉[2] 

机构地区：[1]郧阳师范高等专科学校计算机科学系,湖北丹江口442700 [2]十堰市应用科技学校,湖北丹江口442700

出　　处：《郧阳师范高等专科学校学报》2007年第6期77-79,共3页Journal of Yunyang Teachers College

摘　　要：从大量事务记录中发现有意义的关联规则,可以帮助做出许多商务决策,如分类设计、交叉购物,从而提高销售额度和利润.一种基于链表族数据结构的关联规则挖掘的改进方法,性能明显优于Apriori算法.由于该方法只需访问数据库一次,对于挖掘海量数据其性能尤为明显.Association rules of significant meaning found from lots of affairs documentaries can help to make business decisions, such as, classified design, crossover purchase, so as to raise selling volume and profit. This paper has proposed one improved data mining method of association rules based on chain table data structure, which is better than Apriori calculation. Just visiting data bank once, its property in mining massive data is significant.

关 键 词：数据挖掘 关联规则 支持度 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]