MBiS: an efficient method for mining frequent weighted utility itemsets from quantitative databases

Nguyen Duy Ham, Võ Đình Bảy, Nguyen Thi Hong Minh, Tzung-Pei Hong


In recent years, methods for mining quantitative databases have been proposed. However, the processing time is fairly much, which affects the productivity of intelligent systems in the use of quantitative databases. This study proposes the multi-bit segment (MBiS) structure to store and process tidsets to increase the effeciency of mining frequent weighted utility itemsets (FWUIs) from quantitative databases. With this structure, the calculation of the intersection of tidsets between two itemsets becomes more convenient. Based on this structure, the authors define the MBiS-Tree structure and propose an algorithm for mining FWUIs from quantitative databases. Experimental results for a number of databases show that the proposed method outperforms existing methods.


Dynamic bit vector, frequent itemset, frequent weighted utility itemset, multi-bit segment, tidset.

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DOI: https://doi.org/10.15625/1813-9663/31/1/5154

Journal of Computer Science and Cybernetics ISSN: 1813-9663

Published by Vietnam Academy of Science and Technology