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基于Voronoi图的时间序列线性模式查询算法 被引量:1

Linear pattern query algorithm on time series based on Voronoi diagram
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摘要 时间序列线性模式查询在实际中具有广泛的应用,也是时间序列挖掘的基础。利用Voronoi图的基本原理,提出了一种新的线性模式KL相似性度量,给出了实现线性模式查询的最优算法。 The linear pattern query on time series has wider application,and is the fundamental problems in time series data mining.A new KL similarity measure for the linear pattern query is presented,and an optimal algorithm based on Voronoi diagram is proposed.
作者 秦文
出处 《计算机工程与应用》 CSCD 北大核心 2008年第31期167-168,177,共3页 Computer Engineering and Applications
关键词 时间序列 线性模式 查询 VORONOI图 time series linear pattern query Voronoi diagram
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参考文献9

  • 1Morchen F.Time series knowledge mining[D].Germany:Philipps- University Marburg, 2006.
  • 2Zhou M,Wong M H,Chu K W.A geometrical solution to time series searching invariant to shifting and scaling[J].Knowledge and Information Systems, 2006,9(2) : 202-229.
  • 3Moon Y S,Kim J.A single index approach for time-series subsequence matching that supports moving average transform of arbitrary order[C]//Advances in Knowledge Discovery and Data Mining, 10th Pacific-Asia Conference,PAKDD,Singapore,2006:739-749.
  • 4王国仁,葛健,徐恒宇,郑若石.基于二分频率变换的序列相似性查询处理技术[J].软件学报,2006,17(2):232-241. 被引量:8
  • 5Hetland M L.A survey of recent methods for efficient retrieval of similar time sequences[C]//Data Mining in Time Series Databases, London, 2004 : 23-42.
  • 6Keogh E,Kasetty S.On the need for time series data mining benchmarks:a survey and empirical demonstration[C]//the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,Edmonton,Alberta,Canada,2002:102-111.
  • 7Pratt K B,Fink E.Search for patterns in compressed time series[J]. International Journal of Image and Graphics, 2002,2( 1 ) : 89-106.
  • 8闫相斌,李一军,崔广斌.事件预测的时间序列数据挖掘方法[J].计算机工程,2006,32(5):29-31. 被引量:4
  • 9Prerata F P,Shamos M I.Computational geometry-an introduction[M].New York:Springer-Verlag, 1985.

二级参考文献15

  • 1The human genome project (HGP).2006.http://www.nhgri.nih.gov/
  • 2National Center for Biotechnology Information.Genbank database.2005.http://www.ncbi.nlm.nih.gov/
  • 3Benson DA,Karsh-Mizrachi I,Lipman DJ,Ostell J,Rapp BA,Wheeler DL.Genbank.Nucleic Acids Research,2000,28(1):15-18.
  • 4Gusfield D.Algorithms on Strings,Trees and Sequences:Computer Science and Computational Biology.Cambridge:Cambridge University Press,1997
  • 5Myers E.An O(ND) difference algorithm and itsvariations.Algorithmica,1986,1(2):251-266.
  • 6Myers E.A sublinear algorithm for approximate keyword matching.Algorithmica,1994,12(4-5):345-374.
  • 7Baeza-Yates RA,Navarro G.Faster approximate string matching.Algorithmica,1999,23(2):127-158.
  • 8Kahveci T,Singh AK.An efficient index structure for string databases.In:Apers P,Atzeni P,Ceri S,Paraboschi S,Ramamohanarao K,Snodgrass R,eds.Proc.of the 27th Int'l Conf.on Very Large Data Bases (VLDB 2001).Roma:Morgan Kaufmann Publishers,2001.351-360.
  • 9Sun H,Ozturk O,Ferhatosmanoglu H.CoMRI:A compressed muti-resolution index structure for sequence similarity queries.In:Peter M,Xu Y,ed.Proc.of the 2nd IEEE Computer Society Bioinformatics Conf.(CSB 2003).Califonia:IEEE Computer Society,2003.553-559.
  • 10Ferhatosmanoglu H,Ozturk O.Effective indexing and filtering for similarity search in large biosequence databases.In:Jamil H,Megalooikonomou V,ed.Proc.of the 3rd IEEE Int'l Symp.on BioInformatics and BioEngineering (BIBE 2003).Washington DC:IEEE Computer Society,2003.359-366.

共引文献10

同被引文献9

  • 1潘定,沈钧毅.时态数据挖掘的相似性发现技术[J].软件学报,2007,18(2):246-258. 被引量:41
  • 2Keogh E, Chakrabarti K, Mehrotra Set al.. Locally adaptive dimensionality reduction for indexing large time series databases [C] //Proc ofACM SIGMOD, Santa Barbara, California USA, 2001: 151-162.
  • 3Faloutsos C, Runganathan M, Manolopoulos Y. Fast subsequence matching in time-series databases [C] //Proc ofACM SIGMOD, Minneapolis, Minnesota, USA, 1994: 419-429.
  • 4Han W S, Lee J, Moon Y S, et al.Ranked subsequence matching in time-series databases [C] //Proc of the 33th VLDB Conference, Vienna, Austria, 2007: 423-434.
  • 5Moon Y S, Whang K Y, Loh W K. Duality-based subsequence matching in time-series databases [C] //Proeofl7thlntemational Conference on Data Engineering, Heidelberg, Germany, 2001 : 263.
  • 6Vu K, Hua K A, Cheng H, et al.. A non-linear dimensionality reduction technique for fast similarity search in large databases[C]// Proc ofACM SIGMOD, Chicago, Illinois, USA, 2006: 527-538.
  • 7Li Wei, Keogh E, Van H H, et al.. Atomic Wedgie: efficient query filtering for streaming time series [C] //Proc of Intl Confon Data Mining, Houston, Texax, 2005: 490-497.
  • 8Guttman A. R-trees: a dynamic index structure for spatial searching [C] //Proc ofACM SIGMOD, New York: ACM, 1984: 47-57.
  • 9Hjaltason G R, Samet P. Distance browsing in spatial databases [J]. ACM Transactions on Database Systems, 1999,24 (2): 265-318.

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