A two-phase approach to mine short-periodic high utility itemsets in transactional databases
Article
Article Title | A two-phase approach to mine short-periodic high utility itemsets in transactional databases |
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ERA Journal ID | 36524 |
Article Category | Article |
Authors | Lin, Jerry Chun-Wei (Author), Zhang, Jiexiong (Author), Fournier-Viger, Philippe (Author), Hong, Tzung-Pei (Author) and Zhang, Ji (Author) |
Journal Title | Advanced Engineering Informatics: the science of supporting knowledge-intensive activities |
Journal Citation | 33, pp. 29-43 |
Number of Pages | 15 |
Year | 2017 |
Place of Publication | United Kingdom |
ISSN | 0954-1810 |
1474-0346 | |
1873-5320 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.aei.2017.04.007 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S1474034616300866 |
Abstract | The discovery of high-utility itemsets (HUIs) in transactional databases has attracted much interest from researchers in recent years since it can uncover hidden information that is useful for decision making, and it is widely used in many domains. Nonetheless, traditional methods for high-utility itemset mining (HUIM) utilize the utility measure as sole criterion to determine which item/sets should be presented to the user. These methods ignore the timestamps of transactions and do not consider the period constraint. Hence, these algorithms often finds HUIs that are profitable but that seldom occur in transactions. In this paper, we address this limitation of previous methods by pushing the period constraint in the HUI mining process. A new framework called short-period high-utility itemset mining (SPHUIM) is designed to identify patterns in a transactional database that 1ppear regularly, are profitable, and also yield a high utility under the period constraint. The aim of discovering short-period high-utility itemsets (SPHUI) is hence to identify patterns that are interesting both in terms of period and utility. The paper proposes a baseline two-phase short-period high-utility itemset (SPHUITP) mining algorithm to mine SPHUIs in a level-wise manner. Then, to reduce the search space of the SPHUITP algorithm and speed up the discovery of SPHUIs, two pruning strategies are developed and integrated in the baseline algorithm. The resulting algorithms are denoted as SPHUIMT and SPHUITID, respectively. Substantial experiments both on real-life and synthetic datasets show that the three proposed algorithms can efficiently and effectively discover the complete set of SPHUIs, and that considering the short-period constraint and the utility measure can greatly reduce the number of patterns found. |
Keywords | High-utility itemsets; Periodic high-utility itemsets; SPHUIs; Two-phase; Data mining |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Institution of Origin | University of Southern Queensland |
Byline Affiliations | Harbin Institute of Technology, China |
Peking University, China | |
National University of Kaohsiung, Taiwan | |
School of Agricultural, Computational and Environmental Sciences |
https://research.usq.edu.au/item/q52w1/a-two-phase-approach-to-mine-short-periodic-high-utility-itemsets-in-transactional-databases
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