【作者】 刘燕；

【机构】 闽江学院计算机科学系；

【摘要】 <正>1前言关联规则挖掘是数据挖掘中很重要的研究方向之一,传统的关联规则挖掘方法主要基于支持度和可信度阈值,这些方法在挖掘过程中总是假设数据库中的每个项目具有相同的地位和作用,因而对每个项目作同等处理,这样导致挖掘结果常常包含大量的冗余、无用规则。更多还原

【Abstract】 Discovering association rules is one of the most important tasks in data mining,but most data mining algorithms always assume equal data weights of all items in a database,so all items are treated uniformly,as a result, the number of discovered rules is often so large and many of the rules are useless.Mining Association Rules with Weights is a method to solve the problem.this paper proposes a lower support bound of frequent itemsets with Weights,the bound is calculated easily,it is used to prune to decrease the number of the candidate itemsets in the mining process.更多还原