摘要: 针对关系型数据流,提出一种基于流立方体框架的频繁模式挖掘算法。通过数据流的不断到达动态地创建流立方体来保存近期数据流信息,当用户提出查询请求时在以创建的流立方体基础上进行频繁模式的挖掘计算,返回相应的查询结果,可以快速地挖掘数据流各维之间存在的所有频繁模式。通过分析和实验表明该算法有较好的性能。
关键词:
频繁模式,
流数据,
流立方体,
关系型数据流
Abstract: This paper proposes a new method based on the stream-cube architecture, which is used to deal with relational data stream model. In this algorithm, a dynamical process creates stream-cube to save recent data stream, which continuously arrives with time sequence. Based on the architecture with an analyst’s query, this algorithm can find all of frequent patterns in data stream fast among all dimensions. At last, the analysis and experiments show that this method has good performance.
Key words:
frequent pattern,
data stream,
stream-cube,
relational data stream
中图分类号:
袁正午, 程宇翔, 梁均军, 李林. 基于流立方体的数据流频繁模式挖掘算法[J]. 计算机工程, 2010, 36(22): 43-45.
YUAN Zheng-Wu, CHENG Yu-Xiang, LIANG Jun-Jun, LI Lin. Mining Algorithm for Frequent Pattern in Data Stream Based on Stream-cube[J]. Computer Engineering, 2010, 36(22): 43-45.