BPA: A Bitmap-Prefix-tree Array data structure for frequent closed pattern mining

This paper presents a new efficient data structure, called ldquoa BPA (bitmap-prefix-tree array)rdquo 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 ldquoa collaboration of array, bitmap, and prefix treerdquo, 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.