학술논문
BitApriori: An Apriori-Based Frequent Itemsets Mining Using Bit Streams
Document Type
Conference
Author
Source
2010 International Conference on Information Science and Applications Information Science and Applications (ICISA), 2010 International Conference on. :1-6 Apr, 2010
Subject
Language
ISSN
2162-9048
Abstract
Generating, pruning and counting itemset candidates are important steps in Apriori frequent itemset mining. Unfortunately, their computation time are too expensive. In this paper, we propose a new method using Bit Stream to improve their speed. At the begining, the 1-itemsets are found out and sorted according to the decline of count. By that way, a map of all attributes would be created. After that, each attribute will be presented by 1 bit. At last, the generating and pruning itemset candidates are processed by LOGIC operations which are not cost much of computation time. For experiments we compare our method with some Apriori-based state of the arts.