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关于时间序列相似性概念体系的探讨与研究 被引量:5

Study of the conception of the similarity in time series
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摘要 通过分析高维空间的欧氏几何距离关系并对相似性定义进行拓展 ,提出了一种新的时间序列相似性概念体系 ,即以相似性函数和变换约束函数共同描述两个序列的相似关系 .在这种概念体系中 ,相似性只能是某种相似性函数和变换函数约束下的相似 ,客观的相似性结果依赖于相似性函数和变换函数的主观选取 .新的相似性概念体系可以涵盖以往各种相似性定义 。 By analyzing the Euclidean distance function and its extension, the conception of the similarity in time series describing the relationship of similarity with a uniform similarity function and transformation function was proposed. In the new conception, the similarity existed based on the similarity function and the transformation function. Impersonal result of similarity analysis depended on the subjective selection of the similarity function and the transformation function. The new conceptions can explain all the past definitions and different definitions can be regarded as the features and characters in different areas.
作者 刘世元 江浩
出处 《华中科技大学学报(自然科学版)》 EI CAS CSCD 北大核心 2004年第7期75-76,79,共3页 Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金 国家自然科学基金资助项目 (5 0 2 0 5 0 0 9) 教育部留学回国人员启动基金资助项目
关键词 时间序列 相似性 相似性函数 变换函数 time series similarity similarity function transformation function
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参考文献8

  • 1Agrawal R, Faloutsos C, Swami A. Efficient similarity search in sequence databases. In: Lomet D, ed., Proceedings of the 4th International Conference of Foundations of Data Organization and Algorithms (FODO). Chicago, Illinois,1993. Springer Verlag, 69~84
  • 2Chan K P, Fu A W. Efficient time series matching by wavelets. Proceedings of the 15th IEEE International Conference on Data Engineering, 1999. 126~133
  • 3Keogh E, Pazzani M. Scaling up dynamic time warping for datamining applications. Proceeding of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2000. 285~289
  • 4Perng C S, Wang H, Zhang S R, Parker D S. Landmarks: a new model for similarity-based pattern querying in time series databases. In: Daniele C ed. Data Engineering, Proceedings, Los Alamitos. 2000. 16th International Conference, 2000. 33~42
  • 5Agrawal R, Faloutsos C, Swami A. Efficient similarity search in sequence databases. In: Lomet D, ed., Proceedings of the 4th International Conference of Foundations of Data Organization and Algorithms (FODO). Chicago, Illinois,1993. Springer Verlag, 69~84
  • 6Chan K P, Fu A W. Efficient time series matching by wavelets. Proceedings of the 15th IEEE International Conference on Data Engineering, 1999. 126~133
  • 7Keogh E, Pazzani M. Scaling up dynamic time warping for datamining applications. Proceeding of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2000. 285~289
  • 8Perng C S, Wang H, Zhang S R, Parker D S. Landmarks: a new model for similarity-based pattern querying in time series databases. In: Daniele C ed. Data Engineering, Proceedings, Los Alamitos. 2000. 16th International Conference, 2000. 33~42

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