An Improved Apriori Algorithm for Association Rules of Mining
Apriori --the classical association rules mining algorithm is a way to find out certain potential, regular knowledge from the massive ones. But there are two more serious defects in the data mining process. The first needs many times to scan the business database and the second will inevitably produce a large number of irrelevant candidate sets which seriously occupy the system resources. An improved method is introduced on the basic of the defects above. The improved algorithm only scans the database once, at the same time the discrete data and statistics related are completed, and the final one is to prune the candidate item sets according to the minimum supporting degree and the character of the frequent item sets. After analysis, the improved algorithm reduces the system resources occupied and improves the efficiency and quality.
WEI Yong-qing YANG Ren-hua LIU Pei-yu
Shandong Police College, Jinan 250014,China School of Information Science and Engineering, Shandong Normal University, Jinan 250014,China School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China
国际会议
2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)
济南
英文
942-946
2009-08-14（万方平台首次上网日期，不代表论文的发表时间）