基于窗口内投影的闭合高效用模式挖掘  

Closed High Utility Pattern Mining over Data Stream Based on Projection in the Window

作　　者：李慕航 韩萌[1] 陈志强 武红鑫 张喜龙 LI Muhang;HAN Meng;CHEN Zhiqiang;WU Hongxin;ZHANG Xilong(School of Computer Science and Engineering,North Minzu University,Yinchuan 750021,China)

机构地区：[1]北方民族大学计算机科学与工程学院,银川750021

出　　处：《太原理工大学学报》2022年第2期257-265,共9页Journal of Taiyuan University of Technology

基　　金：国家自然科学基金资助项目(62062004);宁夏自然科学基金资助项目(2020AAC03216)。

摘　　要：提出了一种快速且有效的数据流高效用模式挖掘算法EFIM_Closed_DS.算法基于窗口内投影技术,在每个窗口中使用数据库投影技术以及事务合并方法有效地减少了数据库扫描的代价。使用高效的剪枝技术和有效的闭合项集检测方法能够剪枝大量低效用项集以及非闭合项集。大量实验结果显示,提出的算法比之前最先进的算法在内存和时间上都更为有效。A fast and effective algorithm EFIM_Closed_DS was proposed to mine closed and high utility itemsets in the data stream environment. The algorithm is based on the projection technology in the window, and the database projection technology and transaction merging method are used in each window to effectively reduce the cost of database scanning. Using efficient pruning techniques and effective closed itemset detection methods can prune a large number of low-utility itemsets and non-closed itemsets. A large number of experimental results show that the proposed algorithm is more effective in memory and time than previous state-of-the-art algorithm CHUI_DS.

关 键 词：模式挖掘 数据流 闭合模式 高效用模式挖掘 窗口内投影 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]