计算机工程2012，Vol.38Issue(21)：45-48,4.DOI:10.3969/j.issn.1000-3428.2012.21.012
数据流上的最大频繁项集挖掘方法
Maximal Frequent Itemsets Mining Method over Data Stream
摘要
Abstract
Maximal frequent itemsets is suitable for stream mining, which store most of the information contained in frequent itemsets using less space. This paper focuses on mining maximal frequent itemsets incrementally over streams under landmark model. It designs a simple and compacted data structure to effectively maintain a dynamically selected set of itemsets for quickly node search and pruning. Experimental results on the MUSHROOM and BMS-POS datasets show that this method has higher mining efficiency.关键词
界碑模型/最大频繁项集/数据挖掘/数据流/滑动窗口Key words
landmark model/ maxima! frequent itemsets/ data mining/ data stream/ sliding window分类
信息技术与安全科学引用本文复制引用
李海峰,章宁..数据流上的最大频繁项集挖掘方法[J].计算机工程,2012,38(21):45-48,4.基金项目
国家自然科学基金资助项目(61100112) （61100112）
中央财经大学科研创新团队支持计划基金资助项目 （）
