An efficient and accurate method for evaluating time series similarity
暂无分享,去创建一个
[1] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[2] S. Chiba,et al. Dynamic programming algorithm optimization for spoken word recognition , 1978 .
[3] Wesley W. Chu,et al. An index-based approach for similarity search supporting time warping in large sequence databases , 2001, Proceedings 17th International Conference on Data Engineering.
[4] Paul M. B. Vitányi,et al. Clustering by compression , 2003, IEEE Transactions on Information Theory.
[5] Anil K. Jain,et al. Algorithms for Clustering Data , 1988 .
[6] Donald J. Berndt,et al. Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.
[7] Christos Faloutsos,et al. Efficient retrieval of similar time sequences under time warping , 1998, Proceedings 14th International Conference on Data Engineering.
[8] Lei Chen,et al. On The Marriage of Lp-norms and Edit Distance , 2004, VLDB.
[9] Jiong Yang,et al. CLUSEQ: efficient and effective sequence clustering , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).
[10] G. R. Cross,et al. An improved algorithm to find the length of the longest common subsequence of two strings , 1989, SIGF.
[11] Eamonn Keogh. Exact Indexing of Dynamic Time Warping , 2002, VLDB.
[12] Christos Faloutsos,et al. Fast Time Sequence Indexing for Arbitrary Lp Norms , 2000, VLDB.
[13] Eamonn J. Keogh,et al. Towards parameter-free data mining , 2004, KDD.
[14] F. Itakura,et al. Minimum prediction residual principle applied to speech recognition , 1975 .
[15] Clu-istos Foutsos,et al. Fast subsequence matching in time-series databases , 1994, SIGMOD '94.
[16] Dimitrios Gunopulos,et al. Indexing multi-dimensional time-series with support for multiple distance measures , 2003, KDD '03.
[17] Christos Faloutsos,et al. Efficiently supporting ad hoc queries in large datasets of time sequences , 1997, SIGMOD '97.
[18] Eamonn J. Keogh,et al. On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration , 2002, Data Mining and Knowledge Discovery.
[19] Eamonn J. Keogh,et al. Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases , 2001, Knowledge and Information Systems.
[20] Eamonn J. Keogh,et al. Scaling up Dynamic Time Warping to Massive Dataset , 1999, PKDD.
[21] Eamonn J. Keogh,et al. Making Time-Series Classification More Accurate Using Learned Constraints , 2004, SDM.
[22] Dina Q. Goldin,et al. On Similarity Queries for Time-Series Data: Constraint Specification and Implementation , 1995, CP.
[23] Thomas G. Szymanski,et al. A fast algorithm for computing longest common subsequences , 1977, CACM.
[24] Christos Faloutsos,et al. FTW: fast similarity search under the time warping distance , 2005, PODS.
[25] Renée J. Miller,et al. Similarity search over time-series data using wavelets , 2002, Proceedings 18th International Conference on Data Engineering.
[26] Lei Chen,et al. Robust and fast similarity search for moving object trajectories , 2005, SIGMOD '05.
[27] Dimitrios Gunopulos,et al. Discovering similar multidimensional trajectories , 2002, Proceedings 18th International Conference on Data Engineering.
[28] Ada Wai-Chee Fu,et al. Efficient time series matching by wavelets , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).
[29] Margrit Betke,et al. THE CAMERA MOUSE: PRELIMINARY INVESTIGATION OF AUTOMATED VISUAL TRACKING FOR COMPUTER ACCESS , 2000 .
[30] Christos Faloutsos,et al. Efficient Similarity Search In Sequence Databases , 1993, FODO.
[31] Dennis Shasha,et al. Warping indexes with envelope transforms for query by humming , 2003, SIGMOD '03.