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General Information
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2023 Vol.12(4): 84-92
DOI: 10.18178/ijfcc.2023.12.4.608

An Efficient Approach for Mining Closed High Utility Patterns in the Incremental Database

Ye In Chang*, Po Chun Chuang, Chun Yu Wang, and Yu Hao Liao

Abstract—The utility of an itemset is the product of the profit and the frequency of the itemset in the database. If it is larger than the given threshold, it is defined as the high utility pattern. If there is no superset which has the same frequency as the frequency of its subset, the itemset can be considered as the closed itemset. If the itemset satisfies both the high utility and the closed property, the itemset is defined as the closed high utility itemset/pattern (CHUI). Among those algorithms based on the utility-list structure, the HMiner- Closed algorithm is the most efficient algorithm. However, if the value of the threshold decreases, the number of candidate CHUIs increases and decreases the efficiency of the algorithm. Therefore, in this paper, we propose an efficient algorithm based on a closed-set lattice structure. Our algorithm first finds the closed itemsets and then finds CHUIs in those itemsets. By checking the set relationship between the transactions, we first insert transactions into the closed-set lattice structure. Our algorithm also considers data insertion/deletion in the incremental database. From our performance study, we show that our proposed approach is more efficient than the HMiner-Closed algorithm.

Index Terms—Closed high utility patterns, closed-set lattice, data mining, incremental database, lattice

Y. I. Chang, P. C. Chuang, C. Y. Wang, and Y. H. Liao are with the Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan.
*Correspondence: changyi@mail.cse.nsysu.edu.tw (C.Y.W.)

[PDF]

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.


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)

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