%0 Journal Article
%T Improved apriori mining frequent items algorithm<br>基于频繁项集挖掘算法的改进与研究
%A LIU Bu-zhong
%A <br>刘步中
%J 计算机应用研究
%D 2012
%I 
%X Association rule mining is an important data mining areas of research contents, frequent itemset mining association rules mining is one of the key issues. According to the existing frequent itemset mining algorithm, based on the existing problems, this paper put forward the Apriori algorithm analysis system for Apriori-frequent itemset mining algorithm. The algorithm used overlap strategy to reduce scanning databases, thereby algorithm achieved higher efficiency. Experimental results show that the efficiency of algorithm is 14 times than Apriori system.
%K data mining
%K association rules
%K Inter-Apriori<br>数据挖掘
%K 关联规则
%K 频繁项集挖掘算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=61833B526617F5D599A6C35158544B4D&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=0B39A22176CE99FB&sid=D93AD940782892D0&eid=F18BA6286A889C1C&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10