Finding interesting rules from large sets of discovered association rules
Finding interesting rules from large sets of discovered association rules
复制标题
DOI：
10.1145/191246.191314
复制
发表时间：
1994-11
期刊：
影响因子：
--
通讯作者：
M. Klemettinen;H. Mannila;Pirjo Ronkainen;Hannu (TT) Toivonen;A. I. Verkamo
中科院分区：
文献类型：
--
作者：
M. Klemettinen;H. Mannila;Pirjo Ronkainen;Hannu (TT) Toivonen;A. I. Verkamo
由Agrawal、Imielinski和Swami引入的关联规则是“对于关系的90%的行，如果行在集合W中的列中具有值1，则它在列B中也具有1”的形式的规则。从大量数据中发现关联规则的有效方法是存在的。然而，发现的规则的数量可能非常大，以至于浏览规则集并从中找到感兴趣的规则对用户来说可能相当困难。我们展示了如何一个简单的形式主义的规则模板，可以很容易地描述有趣的规则的结构。我们还给出了规则可视化的例子，并展示了可视化工具如何与规则模板接口。
Association rules, introduced by Agrawal, Imielinski, and Swami, are rules of the form “for 90% of the rows of the relation, if the row has value 1 in the columns in set W, then it has 1 also in column B”. Efficient methods exist for discovering association rules from large collections of data. The number of discovered rules can, however, be so large that browsing the rule set and finding interesting rules from it can be quite difficult for the user. We show how a simple formalism of rule templates makes it possible to easily describe the structure of interesting rules. We also give examples of visualization of rules, and show how a visualization tool interfaces with rule templates.