[1]HU Xue-gang,ZHANG Yuan-yuan.An improved algorithm for mining sequential patterns with time constraints[J].CAAI Transactions on Intelligent Systems,2007,2(2):89-93.
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An improved algorithm for mining sequential patterns with time constraints

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 2 Number of periods: 2007 2 Page number: 89-93 Column: 学术论文—人工智能基础 Public date: 2007-04-25
Title:
An improved algorithm for mining sequential patterns with time constraints
Author(s):
HU Xue-gang; ZHANG Yuan-yuan
School of Computer and Information, Hefei University of Technology, Hefei 230009, China
Keywords:
data mining;  sequential pattern;  time constrain
CLC:
TP182
DOI:
-
Abstract:
An improved time constrained sequential pattern mining algorithm (TSPM) is propo sed, overcoming the problem of traditional sequential mining algorithm whose performance is poor, and result is numerous and short of pertinence. Grap h is introduced to express the frequent 2sequence. It need scan the transactio n database only once, then mapping information related to the mining task int o graph. The graph representation can fully utilize the property of item order i n the mining process, thus improving the generating efficiency of frequent seque nces. Besides it makes use of the positional information of sequence to count su pport, therefore reducing the complexity of time constraints processing, and avo iding the process of testing whether a candidate sequence is contained in a data sequence. Experimental results prove the superiority of the algorithm in time a nd space performance.
References:
［1］ AGRAWAL R, SRIKANT R. Mining sequential patterns［A］. In: Proc of the 11 st Int Conf on Data Engineering［C］. Taipei, China, 1995.
［2］SRIKANT R, AGRAWAL R. Mining sequential patterns: generalizations and perfor mance improvements［A］. In: Proc of the Fifth Int. Conf. on Extending Database Technology (EDBT)［C］. Avignon, France, 1996.
［3］SPADE M. J.An Efficient algorithm for mining frequent sequences［A］. In: Proc eeding of Machine Learning Journal, Special issue on Unsupervised Learning［C］. ［s.l.］,2003.
［4］MASSEGLIA F, CATHALA F，PONCELET P. The psp approach for mining seq uential p atterns［A］. In: Proc.1998 European symp. Principle of data mining and knowledg e discovery (PKDD’98)［C］. Nantes, France, 1998.
［5］HAN Peijian. FreeSpan: frequent patternprojected sequential pattern mini ng ［A ］. In:Proc 2000 Int Conf Knowledge Discovery and Data Mining (KDD.00)［C］. Bos ton, 2000.
［6］PEI J, HAN J, MORTAZAVIASL B, PINTO H, CHEN Q, DAYAL U,HSU M C. P refixSpan: mining sequential patterns efficiently by prefix-projected pattern gr owth［A］. In: Proc 2001 Int Conf Data Engineering (ICDE’01)［C］. Heidelberg, Germany, 2001.
［7］邓明荣，叶福根，史 烈,潘云鹤.挖掘泛化序列模式的一种有效方法［J］. 浙江大学学报,2002，29(4)：415-422.
 DENG Mingrong, YE Fugen, SHI Lie, PAN Yunhe. Efficient algorithm for mining gene ralized sequential patterns［J］. Journal of Zhejiang University, 2002,29(4):415 -42.
［8］朱立运，朱建秋.带时间特征的序列模式挖掘算法TESP［J］.计算机工程，2 004，30(10)，51-54.
?ZHU Liyun, ZHU Jianqiu. Timeenriched equential pattern mining algorithm TESP［ J］ . Computer Engineering, 2004, 30(10), 51-54.
［9］周 斌，吴泉源.序列模式挖掘的一种渐进算法［J］.计算机学报，1999，2 2（10）：882-887.
?ZHOU Bin, WU Quanyuan. An incremental algorithm for mining sequential pattern［ J］. Chinese Journal of Computers,1999,22(10):882-887.
［10］陈金玉，樊兴华.序列模式的一种挖掘算法［J］.重庆大学学报(自然科学版)，2001，24（1）：92-94.
CHEN Jinyu, FAN Xinghua. Algorithm for mining sequential pattern［J］. Journal o f Chongqing University (Natural Science Edition) ,2001,24(1):92-94.
［11］刘月波，陆阶平，刘同明.基于CTID序列模式的一种改进算法［J］.微机发展，2005，15（3）：20-22.
?LIU Yuebo, LU Jieping, LIU Tongming. An improved algorithm for mining sequenti al patterns based on CTID［J］. Microcomputer Development , 2005,15(3):20-22.
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