Efficient chain structure for high-utility sequential pattern mining
Article
Article Title | Efficient chain structure for high-utility sequential pattern mining |
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ERA Journal ID | 210567 |
Article Category | Article |
Authors | Lin, Jerry Chun-Wei (Author), Li, Yuanfa (Author), Fournier-Viger, Philippe (Author), Djenouri, Youcef (Author) and Zhang, Ji (Author) |
Journal Title | IEEE Access |
Journal Citation | 8, pp. 40714-40722 |
Article Number | 9016187 |
Number of Pages | 9 |
Year | 2020 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | Piscataway, United States |
ISSN | 2169-3536 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ACCESS.2020.2976662 |
Web Address (URL) | https://ieeexplore.ieee.org/document/9016187 |
Abstract | High-utility sequential pattern mining (HUSPM) is an emerging topic in data mining, which considers both utility and sequence factors to derive the set of high-utility sequential patterns (HUSPs) from the quantitative databases. Several works have been presented to reduce the computational cost by variants of pruning strategies. In this paper, we present an efficient sequence-utility (SU)-chain structure, which can be used to store more relevant information to improve mining performance. Based on the SU-Chain structure, the existing pruning strategies can also be utilized here to early prune the unpromising candidates and obtain the satisfied HUSPs. Experiments are then compared with the state-of-the-art HUSPM algorithms and the results showed that the SU-Chain-based model can efficiently improve the efficiency performance than the existing HUSPM algorithms in terms of runtime and number of the determined candidates. |
Keywords | high utility sequential pattern mining, sequence, SU-Chain structure, data mining |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Byline Affiliations | Western Norway University of Applied Sciences, Norway |
Harbin Institute of Technology, China | |
SINTEF Digital Microsystems and Nanotechnology, Norway | |
School of Sciences | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q5qq2/efficient-chain-structure-for-high-utility-sequential-pattern-mining
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