SPaMi-FTS: An Efficient Algorithm for Mining Frequent Sequential Patterns

被引：0
作者：
Kadir Febrer-Hernandez, Jose [1 ]
Hernandez-Palancar, Jose [1 ]
Hernandez-Leon, Raudel [1 ]
Feregrino-Uribe, Claudia [2 ]
机构：
[1] Ctr Aplicac Tecnol Avanzada, 7Ma A 21406 E-214 & 216, Havana 12200, Cuba
[2] Inst Nacl Astrofis, Opt & Elect, Puebla 72840, CP, Mexico
来源：
PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014 | 2014年 / 8827卷
关键词：
Data mining; Sequential pattern mining; Frequent sequences;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose a novel algorithm for mining frequent sequences, called SPaMi-FTS (Sequential Pattern Mining based on Frequent Two-Sequences). SPaMi-FTS introduces a new data structure to store the frequent sequences, which together with a new pruning strategy to reduce the number of candidate sequences and a new heuristic to generate them, allows to increase the efficiency of the frequent sequence mining. The experimental results show that the SPaMi-FTS algorithm has better performance than the main algorithms reported to discover frequent sequences.
引用
收藏
页码：470 / 477
页数：8
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