%0 Journal Article
%T Mining Frequent Item Sets with Multiple Convertible Constraints<br>带有多个可转化约束的频繁项集挖掘算法
%A SONG Bao-Li ZHANG Bang-Hua HE Yan-Xiang ZHU Xiao-Feng
%A <br>宋宝莉
%A 张帮华
%A 何炎祥
%A 朱骁峰
%J 计算机科学
%D 2003
%I 
%X Recent work has highlighted the importance of the constraint-based mining paradigm in the context of frequent item sets, associations, correlations. Some research has raised the notion "convertible constraints", and this method can push some constraints into the mining algorithm which essentially can't be pushed. This article has introduced a multiple convertible constraints mining algorithm, which analyzes the constraints by taking advantage of a sample database and then decides a optimal method to process data mining
%K Data mining
%K Multiple constraints
%K Convertible constraints
%K Sample database<br>数据挖掘
%K 事务数据库
%K 可转化约束
%K 频繁项集挖掘算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=0C88FA8F2FDCA6A7&yid=D43C4A19B2EE3C0A&vid=340AC2BF8E7AB4FD&iid=59906B3B2830C2C5&sid=EDA22B444205D04A&eid=7555FB9CC973F695&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=5