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

Author(s):  
Jian Pei ◽  
Jiawei Han ◽  
B. Mortazavi-Asl ◽  
H. Pinto ◽  
Qiming Chen ◽  
...  
2020 ◽  
Vol 36 (1) ◽  
pp. 1-15
Author(s):  
Tran Huy Duong ◽  
Nguyen Truong Thang ◽  
Vu Duc Thi ◽  
Tran The Anh

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.


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

2020 ◽  
Vol 36 (1) ◽  
pp. 1-15
Author(s):  
Tran Huy Duong ◽  
Nguyen Truong Thang ◽  
Vu Duc Thi ◽  
Tran The Anh

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.


Author(s):  
Xinming Gao ◽  
Yongshun Gong ◽  
Tiantian Xu ◽  
Jinhu Lu ◽  
Yuhai Zhao ◽  
...  
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