BPA: A BITMAP-PREFIX-TREE ARRAY DATA STRUCTURE FOR FREQUENT CLOSED PATTERN MINING

被引:2
作者
Wachiramethin, Jugkarin [1 ]
Werapun, Jeeraporn [1 ]
机构
[1] Ladkrabang KMITL, King Mongkuts Inst Technol, Fac Sci, Dept Comp Sci, Bangkok 10520, Thailand
来源
PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6 | 2009年
关键词
Data mining; Closed itemset mining; Multi-dimensional multi-level pattern mining; Bitmap; Prefix tree; Array lists; ASSOCIATION RULES; ITEMSETS;
D O I
10.1109/ICMLC.2009.5212514
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a new efficient data structure, called "a BPA (Bitmap-Prefix-tree Array)" for discovering frequent closed itemset in large transaction database. Recently, most studies have been focused on using an efficient data structure with preprocessing data for the frequent closed itemset mining. Existing prefix-tree-based approach presented the IT-Tree data structure in its complete preprocessing data for the efficient frequent searching but used large memory space and time consuming in the preprocessing step. Lately, another approach introduced the efficient data structure, called "a collaboration of array, bitmap, and prefix tree", to improve storage and time in preprocessing data. However, its preprocessing step was not complete and hence its frequent searching for the frequent closed itemset mining may take more time than that of the IT-Tree-based approach. In this paper, we propose the efficient BPA data structure to enhance not only computation-time and memory-space in the complete preprocessing data but also in those in the frequent searching.
引用
收藏
页码:154 / 160
页数:7
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