标题:The Improved On-Line Analysis Mining for Multi-Dimension Data Based on Association Rules
作者:Yang Bo; Zheng Yongqing
通讯作者:Yang, B
作者机构:[Yang Bo; Zheng Yongqing] Shandong Univ, Coll Comp Sci & Technol, Shandong, Peoples R China.
会议名称:2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR)
会议日期:MAR 06-07, 2010
来源:2010 2ND INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (CAR 2010), VOL 2
出版年:2010
页码:345-348
DOI:10.1109/CAR.2010.5456528
关键词:Multi-Dimension Data; OLAP; Data Mining; Association Rules
摘要:In the paper, we discussed the characteristics of data mining on association rules for multi-dimension data. Then through the multi-dimension data attributes analysis and OLAP operations, we integrate the OLAP and data mining based on their advantages to one method which is called On-Line Analysis Mining (OLAM) [1]. Based on OLAM, an algorithm for multi-dimension data on association rules has been reformed. It can improve the efficiency and flexible of rules searching. Finally, our performance has proved the algorithm.
收录类别:CPCI-S
资源类型:会议论文
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