%0 Journal Article
%T Discovery of Generalized Local Sequential Patterns<br>序列中的一般化局部序列模式发现
%A JIN Xiao-Ming
%A LU Yu-Chang
%A SHI Chun-Yi
%A <br>靳晓明
%A 陆玉昌
%A 石纯一
%J 软件学报
%D 2003
%I 
%X Previous work on pattern discovery in sequence data mainly considers finding global patterns, whereevery record in the temporal sequence contributes to support the patterns. However, local patterns, which arefrequent only in some time periods, are actually very common in practice and the efficient discovery of it ispotentially very useful. This paper presents a method for discovering generalized local sequential patterns with thestructure that supports efficiently locating and counting of the pattern instances and a two-phase method forefficiently mining of local patterns. Experimental results corresponded with the problem definition and verified thesuperiority of the approach.
%K generalized local sequential pattern
%K temporal sequence
%K data mining algorithm<br>一般化局部序列模式
%K 时序序列
%K 数据挖掘算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=E44C3245B8146C02&yid=D43C4A19B2EE3C0A&vid=F3583C8E78166B9E&iid=94C357A881DFC066&sid=714E16F7CF56F343&eid=997CCAFE43D4D200&journal_id=1000-9825&journal_name=软件学报&referenced_num=4&reference_num=10