| 基于数据流的序列模式挖掘算法 |
| |
| 引用本文： | 俞单庆 吉根林. 基于数据流的序列模式挖掘算法[J]. 江南学院学报, 2007, 6(6): 763-768 |
| |
| 作者姓名： | 俞单庆 吉根林 |
| |
| 作者单位： | 南京师范大学数学与计算机科学学院,江苏南京210097 |
| |
| 摘 要： | 为了实现对数据流的序列模式挖掘，提出了基于数据流的序列模式挖掘算法MFSDS-1和MFSDS-2，它们均通过调整入选度的大小来调整保存信息的粒度．算法MFSDS-2利用分层存储结构，不仅能更好地保存序列信息，而且可以通过与全局序列模式的对比得到当前活动的一些异常序列模式．实验结果表明，基于分层存储的算法MFSDS-2的效率比算法MSFDS-1高．
|
| 关 键 词： | 序列模式挖掘 频繁序列 数据流 |
| 文章编号： | 1671-7147（2007）06-0763-06 |
| 收稿时间： | 2007-05-10 |
| 修稿时间： | 2007-06-13 |
Mining Frequent Sequence from .Data Stream |
| |
| YU Shan-qing, JI Gen-lin. Mining Frequent Sequence from .Data Stream[J]. Journal of Jiangnan College, 2007, 6(6): 763-768 |
| |
| Authors: | YU Shan-qing JI Gen-lin |
| |
| Abstract: | Although sequence pattern mining has been deeply studied, it is a challenge to extend to data streams. In the paper, algorithm MFSDS-1 and MFSDS-2 are presented for mining sequential patterns from data stream. Both of the algorithms use the storage of elected sequences which are accommodated by the elected rate. In algorithm MFSDS-2 a new structure based on levels is proposed, which not only can store the sequence well, but also can be used to find the abnormal sequence. The experiments results show that MFSDS- 2 is more efficient than MFSDS-1. |
| |
| Keywords: | sequence pattern mining frequent sequenee data stream |
| 本文献已被 维普 等数据库收录！ |
