An Efficient Aggregation Method for the Symbolic Representation of Temporal Data

Symbolic representations are a useful tool for the dimension reduction of temporal data, allowing for the efficient storage of and information retrieval from time series. They can also enhance the training of machine learning algorithms on time series data through noise reduction and reduced sensiti...

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Veröffentlicht in:	ACM transactions on knowledge discovery from data 2023-02, Vol.17 (1), p.1-22, Article 5
Hauptverfasser:	Chen, Xinye, Güttel, Stefan
Format:	Artikel
Sprache:	eng
Schlagworte:	Cluster analysis Computing methodologies Dimensionality reduction and manifold learning Learning latent representations Machine learning algorithms
Online-Zugang:	Volltext
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