A review on distance based time series classification
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2018/11/01
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Indian UGC (journal)
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Refrences113
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Citations93
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Amaia Abanda ORCID (unauthenticated)
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Usue Mori
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Jose A. Lozano
Cite
Abanda, Amaia, et al. “A Review on Distance Based Time Series Classification”. Data Mining and Knowledge Discovery, vol. 33, no. 2, 2018, pp. 378-12, https://doi.org/10.1007/s10618-018-0596-4.
Abanda, A., Mori, U., & Lozano, J. A. (2018). A review on distance based time series classification. Data Mining and Knowledge Discovery, 33(2), 378-412. https://doi.org/10.1007/s10618-018-0596-4
Abanda, Amaia, Usue Mori, and Jose A. Lozano. “A Review on Distance Based Time Series Classification”. Data Mining and Knowledge Discovery 33, no. 2 (2018): 378-412. https://doi.org/10.1007/s10618-018-0596-4.
Abanda A, Mori U, Lozano JA. A review on distance based time series classification. Data Mining and Knowledge Discovery. 2018;33(2):378-412.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Science (General)
Cybernetics
Information theory
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Mechanical engineering and machinery
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Reliable early classification of time series based on discriminating the classes over time | Data Mining and Knowledge Discovery |
| 34 | 2017 |
| The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances | Data Mining and Knowledge Discovery |
| 511 | 2017 |
| 10.1109/TIT.2016.2598574 | IEEE Transactions on Information Theory |
| 2016 | |
| Support vector-based algorithms with weighted dynamic time warping kernel function for time series classification | Knowledge-Based Systems |
| 34 | 2015 |
| Using dynamic time warping distances as features for improved time series classification | Data Mining and Knowledge Discovery |
| 149 | 2015 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Bake off redux: a review and experimental evaluation of recent time series classification algorithms | Data Mining and Knowledge Discovery |
| 2024 | |
| Microclimate spatio-temporal prediction using deep learning and land use data | Building and Environment |
| 2024 | |
| Improved collaborative filtering for cross-store demand forecasting | Computers & Industrial Engineering |
| 2024 | |
| Interpretable synthetic signals for explainable one-class time-series classification | Engineering Applications of Artificial Intelligence |
| 2024 | |
| Distance-based one-class time-series classification approach using local cluster balance | Expert Systems with Applications |
| 2 | 2024 |
Citations Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 48
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Learning Kullback-Leibler Divergence-Based Gaussian Model for Multivariate Time Series Classification and was published in 2019. The most recent citation comes from a 2024 study titled Bake off redux: a review and experimental evaluation of recent time series classification algorithms. This article reached its peak citation in 2023, with 27 citations. It has been cited in 65 different journals, 27% of which are open access. Among related journals, the IEEE Access cited this research the most, with 7 citations. The chart below illustrates the annual citation trends for this article.