iSAX: indexing and mining terabyte sized time series
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Summary
This work shows how a novel multi-resolution symbolic representation can be used to index datasets which are several orders of magnitude larger than anything else considered in the literature, allowing for the exact mining of truly massive real world datasets.
- Type
- article
- Published
- 2008-08-24
- Cited by
- 428
- References
- 18
- OpenAlex
- https://openalex.org/W2077720176
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:5933532
Keywords
Computer science, Search engine indexing, Exploit, Data mining, Representation (politics)
References
- Three Myths about Dynamic Time Warping Data Mining
- Adaptive query processing for time-series data
- Indexing spatio-temporal trajectories with Chebyshev polynomials
- Compression of ECG signals by optimized quantization of discrete cosine transform coefficients.
- The TS-tree: efficient time series search and retrieval
- Fast time series classification using numerosity reduction
- Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases
- Atlas of States of Sleep and Wakefulness in Infants and Children
- A wavelet transform-based ECG compression method guaranteeing desired signal quality
- A multiresolution symbolic representation of time series
- Fast subsequence matching in time-series databases
- Experiencing SAX: a novel symbolic representation of time series
- Discovery of climate indices using clustering
- Using Signature Files for Querying Time-Series Data
Cited by
- Time series data mining for the Gaia variability analysis
- Knowledge Extraction in Video Through the Interaction Analysis of Activities Knowledge Extraction in Video Through the Interaction Analysis of Activities
- Probabilistic Process Monitoring in Process-Aware Information Systems
- Indexation de séquences de descripteurs
- Multiresolution Motif Discovery in Time Series
- Fast Algorithms for Mining Co-evolving Time Series
- Relational Implementation of Multi-dimensional Indexes for Time Series
- Modeling and Querying Data Series and Data Streams with Uncertainty
- A Symbolic Representation for Trajectory Data
- Intelligent Data Engineering and Automated Learning – IDEAL 2020: 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II
- Multiobjective time series matching and classification
- Time series representation and similarity based on local autopatterns
- Similarity Search in High-dimensional Spaces with Applications to Time Series Data Mining and Information Retrieval
- Using dynamic time warping distances as features for improved time series classification
- Knowledge Discovery from Time Series
- Automatically estimating iSAX parameters
- New Approaches for Data-mining and Classification of Mental Disorder in Brain Imaging Data
- Improved particle swarm optimization for fuzzy based stock market turning points prediction
- Formalism for a multiresolution time series database model
- Similarity processing in multi-observation data
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