DATABASE ENCODING AND AN ANTI-APRIORI ALGORITHM FOR ASSOCIATION RULES MINING

摘要：

A method for encoding database is put forward in this paper. By this way, a record is denoted by only one binary number and so the size of the database is reduced sharply. If the database-encoding algorithm is used into some known modified algorithms, the efficiency will be improved remarkably. At the meantime, a new algorithm, anti-Apriori,which based on the proposed encoding method is introduced either. By using some properties of numbers, the itemsets of the database can be transformed into numerical fields.Different from the Apriori algorithm, the new one discovers the association rules from the largest frequent itemset at first,and then all sub itemset, which are also frequent, will be gained without any farther calculation, and all the other small frequent itemset that must be generated in the Apriori be omitted, and the times of the database scan is also reduced.Test results show the new algorithm based on the encoding database has a lower complexity of time and space.

关键词： Anti-Apriori algorithm association rules data mining database encoding

作者: TONG WANG PI-LIAN HE

作者单位: The Vocational Technique Instruction College, TianJin University, Tianjin 30072, China;The Computer The Computer Science & Technology College, TianJin University, Tianjin 30072, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 1195-1198

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）