An Algorithm for Mining High Utility Sequential Patterns with Time Interval
| Autor: | Tran Huy Duong, Demetrovics Janos, Vu Duc Thi, Nguyen Truong Thang, Tran The Anh |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
010201 computation theory & mathematics Computer science 0202 electrical engineering electronic engineering information engineering Interval (graph theory) 020201 artificial intelligence & image processing 0102 computer and information sciences 02 engineering and technology 01 natural sciences Algorithm |
| Zdroj: | Cybernetics and Information Technologies. 19:3-16 |
| ISSN: | 1314-4081 |
| Popis: | Mining High Utility Sequential Patterns (HUSP) is an emerging topic in data mining which attracts many researchers. The HUSP mining algorithms can extract sequential patterns having high utility (importance) in a quantitative sequence database. In real world applications, the time intervals between elements are also very important. However, recent HUSP mining algorithms cannot extract sequential patterns with time intervals between elements. Thus, in this paper, we propose an algorithm for mining high utility sequential patterns with the time interval problem. We consider not only sequential patterns’ utilities, but also their time intervals. The sequence weight utility value is used to ensure the important downward closure property. Besides that, we use four time constraints for dealing with time interval in the sequence to extract more meaningful patterns. Experimental results show that our proposed method is efficient and effective in mining high utility sequential pattern with time intervals. |
| Databáze: | OpenAIRE |
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