PrefixSpan,: mining sequential patterns efficiently by prefix-projected pattern growth

2005 ◽  
Author(s):  
Jian Pei ◽  
Jiawei Han ◽  
B. Mortazavi-Asl ◽  
H. Pinto ◽  
Qiming Chen ◽  
...  
Keyword(s):  
Sequential Patterns ◽  
Pattern Growth

scholarly journals HIGH UTILITY ITEM INTERVAL SEQUENTIAL PATTERN MINING ALGORITHM

2020 ◽  
Vol 36 (1) ◽  
pp. 1-15
Author(s):  
Tran Huy Duong ◽  
Nguyen Truong Thang ◽  
Vu Duc Thi ◽  
Tran The Anh
Keyword(s):  
Data Mining ◽  
Pattern Mining ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Sequential Patterns ◽  
Sequence Database ◽  
Mining Algorithm ◽  
Pattern Growth ◽  
High Utility ◽  
Growth Approach

High utility sequential pattern mining is a popular topic in data mining with the main purpose is to extract sequential patterns with high utility in the sequence database. Many recent works have proposed methods to solve this problem. However, most of them does not consider item intervals of sequential patterns which can lead to the extraction of sequential patterns with too long item interval, thus making little sense. In this paper, we propose a High Utility Item Interval Sequential Pattern (HUISP) algorithm to solve this problem. Our algorithm uses pattern growth approach and some techniques to increase algorithm's performance.

scholarly journals Mining sequential patterns by pattern-growth: the PrefixSpan approach

2004 ◽  
Vol 16 (11) ◽  
pp. 1424-1440 ◽  
Author(s):  
Jian Pei ◽  
Jiawei Han ◽  
B. Mortazavi-Asl ◽  
Jianyong Wang ◽  
H. Pinto ◽  
...  
Keyword(s):  
Sequential Patterns ◽  
Pattern Growth

scholarly journals HIGH UTILITY ITEM INTERVAL SEQUENTIAL PATTERN MINING ALGORITHM

2020 ◽  
Vol 36 (1) ◽  
pp. 1-15
Author(s):  
Tran Huy Duong ◽  
Nguyen Truong Thang ◽  
Vu Duc Thi ◽  
Tran The Anh
Keyword(s):  
Data Mining ◽  
Pattern Mining ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Sequential Patterns ◽  
Sequence Database ◽  
Mining Algorithm ◽  
Pattern Growth ◽  
High Utility ◽  
Growth Approach

High utility sequential pattern mining is a popular topic in data mining with the main purpose is to extract sequential patterns with high utility in the sequence database. Many recent works have proposed methods to solve this problem. However, most of them does not consider item intervals of sequential patterns which can lead to the extraction of sequential patterns with too long item interval, thus making little sense. In this paper, we propose a High Utility Item Interval Sequential Pattern (HUISP) algorithm to solve this problem. Our algorithm uses pattern growth approach and some techniques to increase algorithm's performance.

Toward to Better Structure and Constraint to Mine Negative Sequential Patterns

2020 ◽  
pp. 1-15
Author(s):  
Xinming Gao ◽  
Yongshun Gong ◽  
Tiantian Xu ◽  
Jinhu Lu ◽  
Yuhai Zhao ◽  
...  
Keyword(s):  
Sequential Patterns
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