Algorithms for clustering data
Algorithms for clustering data
Fundamentals of speech recognition
Fundamentals of speech recognition
Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficiently supporting ad hoc queries in large datasets of time sequences
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Dimensionality reduction for similarity searching in dynamic databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Scaling up dynamic time warping for datamining applications
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A comparison of DFT and DWT based similarity search in time-series databases
Proceedings of the ninth international conference on Information and knowledge management
Information Retrieval
Machine Learning
Locally adaptive dimensionality reduction for indexing large time series databases
ACM Transactions on Database Systems (TODS)
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
An Index-Based Approach for Similarity Search Supporting Time Warping in Large Sequence Databases
Proceedings of the 17th International Conference on Data Engineering
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
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
Indexing spatio-temporal trajectories with Chebyshev polynomials
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
FTW: fast similarity search under the time warping distance
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Effective and efficient similarity search in time series
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Exact indexing of dynamic time warping
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
IEEE Transactions on Computers
On the marriage of Lp-norms and edit distance
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
MSPtool: A Versatile Tool for Mass Spectrometry Data Preprocessing
CBMS '08 Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems
Clustering of time series data-a survey
Pattern Recognition
Low-voltage electricity customer profiling based on load data clustering
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Efficient classification based on multi-scale traffic data extraction patterns of cellular networks
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Weighted dynamic time warping for time series classification
Pattern Recognition
ACM Computing Surveys (CSUR)
Feature selection for classification of oscillating time series
Expert Systems: The Journal of Knowledge Engineering
Possibilistic nonlinear dynamical analysis for pattern recognition
Pattern Recognition
Using derivatives in time series classification
Data Mining and Knowledge Discovery
A representation of time series based on implicit polynomial curve
Pattern Recognition Letters
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Similarity search and detection is a central problem in time series data processing and management. Most approaches to this problem have been developed around the notion of dynamic time warping, whereas several dimensionality reduction techniques have been proposed to improve the efficiency of similarity searches. Due to the continuous increasing of sources of time series data and the cruciality of real-world applications that use such data, we believe there is a challenging demand for supporting similarity detection in time series in a both accurate and fast way. Our proposal is to define a concise yet feature-rich representation of time series, on which the dynamic time warping can be applied for effective and efficient similarity detection of time series. We present the Derivative time series Segment Approximation (DSA) representation model, which originally features derivative estimation, segmentation and segment approximation to provide both high sensitivity in capturing the main trends of time series and data compression. We extensively compare DSA with state-of-the-art similarity methods and dimensionality reduction techniques in clustering and classification frameworks. Experimental evidence from effectiveness and efficiency tests on various datasets shows that DSA is well-suited to support both accurate and fast similarity detection.