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BPA: A bitmap-prefix-tree array data structure for frequent closed pattern mining
Author(s)
Wachiramethin, Jugkarin
Werapun, Jeeraporn
Date Issued
January 1, 2009
Type
Conference Paper
Abstract
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. © 2009 IEEE.
Citation
Proceedings of the 2009 International Conference on Machine Learning and Cybernetics, 1, 154-160, 2009