High-utility Sequential Pattern Mining
High-Utility Sequential Pattern Mining is a data mining methodology that identifies sequences of events or items with significantly high utility values, where utility reflects user-defined measures such as profit, importance, or weight, thereby extending traditional sequential pattern mining by incorporating quantitative utility information to discover more meaningful and valuable patterns.
81
Publications
4.2K
Citations
178
Authors
105
Institutions
Publications per year
2017–2026
55
Parents
81
1–5 of 81
178
Western Norway University of Applied Sciences, Norway
17 publications · 1.1K citations
16
h-index
15
h-index
8
h-index
8
h-index
6
h-index
1–5 of 178
105

Harbin Institute of Technology
Harbin, China
20 h-index
46 publications
2.1K citations
Western Norway University of Applied Sciences
Bergen, Norway
11 h-index
11 publications
483 citations

Vietnam National University Ho Chi Minh City
Ho Chi Minh City, Vietnam
9 h-index
12 publications
370 citations

Shenzhen Institute of Information Technology
Shenzhen, China
9 h-index
13 publications
721 citations

Jinan University
Guangzhou, China
8 h-index
11 publications
421 citations
Ho Chi Minh City University of Science
Ho Chi Minh City, Vietnam
7 h-index
10 publications
254 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
6 h-index
11 publications
534 citations
University of Illinois Chicago
Chicago, United States
6 h-index
6 publications
219 citations
1–8 of 105
13 publications · 950 citations
12
h-index
9 publications · 359 citations
9
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9 publications · 392 citations
9
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7 publications · 294 citations
7
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TKDD · 3 publications · 68 citations
3
h-index
1–5