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

Authors

  • Nguyen Duy Ham Department of Math & Informatics, University of People’s Security, Hochiminh City, Vietnam
  • Võ Đình Bảy Faculty of Information Technology, Hochiminh City University of Technology, Vietnam
  • Nguyen Thi Hong Minh School of Graduate Studies, Vietnam National University, Hanoi, Vietnam
  • Tzung-Pei Hong Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan, ROC

DOI:

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

Keywords:

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

Abstract

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.

Metrics

Metrics Loading ...

Author Biography

Võ Đình Bảy, Faculty of Information Technology, Hochiminh City University of Technology, Vietnam

Trưởng phòng Quản lý khoa học và công nghệ thông tin

Downloads

Published

2015-03-16

How to Cite

[1]
N. D. Ham, V. Đình Bảy, N. T. H. Minh, and T.-P. Hong, “MBiS: an efficient method for mining frequent weighted utility itemsets from quantitative databases”, JCC, vol. 31, no. 1, pp. 17–30, Mar. 2015.

Issue

Section

Computer Science