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

页码：470 / 477

页数：8

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