Data Stream Frequent Closed Item Sets Mining Based on Fast Sliding Window

摘要：

According to the mobility and continuity of the flow of data streams, this paper presents an algorithm called NSWR to mine the frequent item sets from a fast sliding window over data streams and it meets peoples needs of getting the frequent item sets over data that recently arrive. NWSR, using an effective bit-sequence representation of items based on the data stream sliding window, helps to store data; to support different support threshold value inquiry through hash-table-based frequent closed item sets results query method; to offer screening method based on the classification of closed item sets for reducing the number of item sets that need closure judgments, effectively reducing the computational complexity. Experiments show that the algorithm has better time and space efficiency.

关键词： data mining data stream frequent closed item sets sliding window

作者: Chen Zhihua Luo Jun

作者单位: Computer&Network Center Guangdong Polytechnic Normal University Guangzhou,China

会议类型: 国际会议

会议名称: 2011 3nd International Conference on Mechanical and Electronics Engineering(2011年第三届机械与电子工程国际会议 ICMEE2011)

会议地点: 合肥

会议语种:英文

页码: 3702-3707

在线出版日期: 2011-09-23（万方平台首次上网日期，不代表论文的发表时间）