Abstract
In this paper we introduce a novel approach for fast retrieval of temporal patterns from time series data. This method constructs firstly an index over key subsequences, using subdimensional clustering. Then, during the querying process, rather than scanning the whole database, to extract relevant answers for a given query, our method suggests the traversal of the index represented as centroids of clusters, and search for similar subsequences.
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Benabderrahmane, S. (2015). Temporal Constraints and Sub-Dimensional Clustering for Fast Similarity Search over Time Series Data. Application to Information Retrieval Tasks.. In: Selvaraj, H., Zydek, D., Chmaj, G. (eds) Progress in Systems Engineering. Advances in Intelligent Systems and Computing, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-319-08422-0_40
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DOI: https://doi.org/10.1007/978-3-319-08422-0_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08421-3
Online ISBN: 978-3-319-08422-0
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