数据流频繁模式挖掘

Data Stream Frequent Pattern Mining

近年来,数据流挖掘越来越引起研究人员的关注,已逐渐成为许多领域有用的工具.如何利用有限的存储空间高效地挖掘出频繁模式已成为数据流挖掘的基本问题,具有很强的现实意义和理论价值.本文分析了国内外的各种数据流频繁模式挖掘算法,并指出这些算法的分类.通过综合分析最终给出了未来的研究发展方向.

Data stream mining has attracted many researchers＇ attention and has become a useful tool for many fields.A fundamental problem is how to use the limited storage space to mine frequent pattern efficiently.Various frequent pattern mining algorithms are analyzed and their classifications are pointed out in this paper.Finally,future directions in data mining stream research are discussed.