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SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Haar Wavelets for Efficient Similarity Search of Time-Series: With and Without Time Warping
IEEE Transactions on Knowledge and Data Engineering
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Landmarks: A New Model for Similarity-Based Pattern Querying in Time Series Databases
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Data Mining and Knowledge Discovery
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
A dimensionality reduction technique for efficient similarity analysis of time series databases
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Exact indexing of dynamic time warping
Knowledge and Information Systems
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Clustering of time-series subsequences is meaningless: implications for previous and future research
Knowledge and Information Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Fast time series classification using numerosity reduction
ICML '06 Proceedings of the 23rd international conference on Machine learning
Indexing Multidimensional Time-Series
The VLDB Journal — The International Journal on Very Large Data Bases
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Intelligent stock trading system by turning point confirming and probabilistic reasoning
Expert Systems with Applications: An International Journal
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Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
On the marriage of Lp-norms and edit distance
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Indexable PLA for efficient similarity search
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Matching of quasi-periodic time series patterns by exchange of block-sorting signatures
Pattern Recognition Letters
Toward accurate dynamic time warping in linear time and space
Intelligent Data Analysis
Scaling and time warping in time series querying
The VLDB Journal — The International Journal on Very Large Data Bases
iSAX: indexing and mining terabyte sized time series
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A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Bounded similarity querying for time-series data
Information and Computation
Reduced data similarity-based matching for time series patterns alignment
Pattern Recognition Letters
Discrete wavelet transform-based time series analysis and mining
ACM Computing Surveys (CSUR)
A review on time series data mining
Engineering Applications of Artificial Intelligence
A novel clustering method on time series data
Expert Systems with Applications: An International Journal
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Journal of Experimental & Theoretical Artificial Intelligence
Similarity search on time series based on threshold queries
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Finding time series discords based on haar transform
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
ACM Computing Surveys (CSUR)
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Due to the characteristics of noise and volatility, two similar time series always appear in diverse kinds of distortions, which usually are considered as the combinations of the following basic transformations: noise, amplitude shift, amplitude scaling, temporal scaling, and linear drift. In this paper, a novel similarity measure (SIMshape) invariant to these basic distortions and any combinations of them is proposed. It is parameter-free and easy to implement. Specifically, a multi-scale shape approximation for time series based on Discrete Haar Wavelet Transform, key point extraction and symbolization is presented first; then, based on this proposed representation and a scale-weight factor, a robust similarity measure is proposed. The novelty of SIMshape lies in two aspects as follows: (a) symbolizing key points sequence extracted from approximate wavelet coefficients; (b) adding the scale-weight factor and shape similarity in the similarity criterion. To show the effectiveness and efficiency, SIMshape is compared with other popular methods Euclidean Distance (ED), LB_keogh, Complexity Invariant Distance (CID), and ASEAL (Approximate Shape Exchange ALgorithm) using two indices: the number of kinds of distortions and the degree of distortion. Obtained results show that compared with ED, CID, LB_keogh, and ASEAL, SIMshape has better robustness in synthetic data, and shows better performance in real time series classification.