doi: 10.18178/ijfcc.2023.12.4.608
An Efficient Approach for Mining Closed High Utility Patterns in the Incremental Database
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Chun Yu Wang
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- Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Abstract
The utility of an itemset is the product of the profitand the frequency of the itemset in the database. If it is largerthan the given threshold, it is defined as the high utility pattern.If there is no superset which has the same frequency as thefrequency of its subset, the itemset can be considered as theclosed itemset. If the itemset satisfies both the high utility andthe closed property, the itemset is defined as the closed highutility itemset/pattern (CHUI). Among those algorithms basedon the utility-list structure, the HMiner- Closed algorithm is themost efficient algorithm. However, if the value of the thresholddecreases, the number of candidate CHUIs increases anddecreases the efficiency of the algorithm. Therefore, in thispaper, we propose an efficient algorithm based on a closed-setlattice structure. Our algorithm first finds the closed itemsetsand then finds CHUIs in those itemsets. By checking the setrelationship between the transactions, we first inserttransactions into the closed-set lattice structure. Our algorithmalso considers data insertion/deletion in the incrementaldatabase. From our performance study, we show that ourproposed approach is more efficient than the HMiner-Closedalgorithm.
Keywords
- Closed high utility patterns
- closed-set lattice
- data mining
- incremental database
- lattice
How to Cite
Ye In Chang, Po Chun Chuang, Chun Yu Wang, and Yu Hao Liao, "An Efficient Approach for Mining Closed High Utility Patterns in the Incremental Database," International Journal of Future Computer and Communication, vol. 12, no. 4, pp. 84-92, 2023. https://doi.org/ 10.18178/ijfcc.2023.12.4.608
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).