Sequential pattern mining algorithms review

被引：11

作者：

Kadir Febrer-Hernandez, Jose ^{[1
]}

Hernandez-Palancar, Jose ^{[1
]}

机构：

[1] Adv Technol Applicat Ctr, Havana 12200, Cuba

来源：

INTELLIGENT DATA ANALYSIS | 2012年 / 16卷 / 03期

关键词：

Data mining; sequence mining; frequent sequence; pattern growth;

D O I：

10.3233/IDA-2012-0533

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

From the beginning of sequential pattern mining to the present, this field has received important attention within the data mining area, because it has a wide application in several significant computational problems. Many algorithms have been created and several techniques have been used with the objective of improving the discovery of the frequent sequence set. In this paper we present the main characteristics of some of the most important sequential pattern mining algorithms. Also, we show a comparative performance study among these algorithms.

引用

页码：451 / 466

页数：16

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