Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
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SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
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PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
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Relevance feedback retrieval of time series data
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SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
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FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
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ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
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ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
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PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
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VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
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KDEX '99 Proceedings of the 1999 Workshop on Knowledge and Data Engineering Exchange
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IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
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CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
Efficient Subsequence Matching in Time Series Databases Under Time and Amplitude Transformations
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
A Multiresolution Symbolic Representation of Time Series
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
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Intelligent Data Analysis
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Information Systems
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ADC '10 Proceedings of the Twenty-First Australasian Conference on Database Technologies - Volume 104
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AMR'05 Proceedings of the Third international conference on Adaptive Multimedia Retrieval: user, context, and feedback
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Engineering Applications of Artificial Intelligence
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Expert Systems with Applications: An International Journal
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We address the problem of similarity search in large time series databases. We introduce a novel-dimensionality reduction technique that supports an indexing algorithm that is more than an order of magnitude faster than the previous best known method. In addition to being much faster our approach has numerous other advantages. It is simple to understand and implement, allows more flexible distance measures including weighted Euclidean queries and the index can be built in linear time. We call our approach PCA-indexing (Piece-wise Constant Approximation) and experimentally validate it on space telemetry, financial, astronomical, medical and synthetic data.