AN ALGORITHM OF ASSOCIATION RULES DOUBLE SEARCH MINING BASED ON BINARY

摘要：

In order to solve these problems how to easily generate candidate frequent item sets and fast compute support of candidate item sets, an algorithm of association rules mining based on binary has been introduced. However, one presented binary mining algorithm is only suitable for mining some relative short frequent item sets since the way of generating candidate item sets is also similar to Apriori, another is only suitable for mining long frequent item sets, which generates candidate item sets by up-down search strategy. And so aiming to mining general frequent item sets, this paper proposes an algorithm of association rules double search mining based on binary, which is different from tradition association rules mining algorithm based on double search strategy. The algorithm doesnt use combination of set theory to generate candidate item sets but binary logic operation that is also used to compute support of candidate item sets, which can use character digital to reduce the number of scanned transaction. The algorithm gets rid of shortage about some presented algorithms based on binary. The experiment based on above three algorithms indicates that the efficiency about double search strategy is fast and efficient when mining general frequent item sets which arent confined.

关键词： Data mining association rules binary double search digital transaction

作者: GANG FANG ZU-KUAN WEI QIAN YIN

作者单位: School of Computer Science and Engineering, University of Electronic Science and Technology of China College of Information Science and Technology, Beijing Normal University, Beijing 100875, P.R.China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 184-189

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）