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网络数据流分析方法 被引量：2

ANALYSIS METHODS FOR NETWORK DATA STREAM
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摘要 介绍网络数据流中最主要的数据流挖掘技术。 The analysis methods of network data stream are introduced, in which the most important part is the data stream mining technology. It has of extensive practical background and application value to research this technology .
作者 罗莎 朱威 王培源 邹彤 郭唐永
机构地区 中国地震局地震研究所
出处 《大地测量与地球动力学》 CSCD 北大核心 2011年第B06期146-148,151,共4页 Journal of Geodesy and Geodynamics
关键词 数据流 网络数据 分析 数据流挖掘 技术 data stream network data analysis data stream mining technology
分类号 TP314 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献11

  • 1司开君,毛宇光.一种新的基于数据流的数据模型[J].计算机技术与发展,2007,17(1):1-3. 被引量：7
  • 2孙晓华.数据流挖掘技术研究[D].哈尔滨理工大学,2007.
  • 3Guha S, et al. Clustering data streams [ A ]. In Proceedings of the Annual Symposium on Foundations of Computer Science[ C]. IEEE, 2000.
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二级参考文献24

  • 1Babcock B, et al. Models and Issues in Data Streams[A]. Proc. Of the 21st ACM SIGACT-SIGMOD-SIGART Symp. On Principles of Database Systems[C]. Madison:ACM Press, 2002.1-16.
  • 2Garofalakis M, Gehrke J, Rastogi R. Querying and Mining Data Stream:You Only Get One Look,A Tutorial[A]. Franklin MJ, Moon B, Ailamaki A. Proc. of the 2002 ACM SIGMOD Int'l Conf. on Management of Data[C]. Madison:ACM Press, 2002. 635.
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  • 8P Indyk. Stable Distributions, Pseudorandom Generators, Embeddings and Data Stream Computation[C].Proc. of the 2000 Annual IEEE Symp. on Foundations of Computer Science, 2000. 437-448,
  • 9Gibbons PB, Matias Y, Poosala V. Fast Incremental Maintenance of Approximate Histograms[A]. Jarke M, Carey MJ, Dittrich KR, et al. VLDB'97, Proc. of the 23rd Int'l Conf. on Very Large Data Bases[C]. Athens:Morgan Kaufmann, 1997. 466-475.
  • 10Ioannidis Y, Poosala V. Balancing Histogram Optimality and Practicality for Query Result Size Estimation[J]. SIGMOD Record, 1995, 24(2):233-244.

共引文献16

同被引文献15

引证文献2

二级引证文献5

大地测量与地球动力学
2011年 第B06期

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