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Diverse relevance feedback for time series with autoencoder based summarizations
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Eravci, Bahaeddin and Ferhatosmanoglu, Hakan (2018) Diverse relevance feedback for time series with autoencoder based summarizations. IEEE Transactions on Knowledge and Data Engineering, 30 (12). 2298 -2311. doi:10.1109/TKDE.2018.2820119
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Official URL: http://dx.doi.org/10.1109/TKDE.2018.2820119
Abstract
We present a relevance feedback based browsing methodology using different representations for time series data. The outperforming representation type, e.g., among dual-tree complex wavelet transformation, Fourier, symbolic aggregate approximation (SAX), is learned based on user annotations of the presented query results with representation feedback. We present the use of autoencoder type neural networks to summarize time series or its representations into sparse vectors, which serves as another representation learned from the data. Experiments on 85 real data sets confirm that diversity in the result set increases precision, representation feedback incorporates item diversity and helps to identify the appropriate representation. The results also illustrate that the autoencoders can enhance the base representations, and achieve comparably accurate results with reduced data sizes.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||||
| Divisions: | Faculty of Science > Computer Science | ||||||||
| Library of Congress Subject Headings (LCSH): | Algorithms, Time-series analysis -- Classification -- Mathematical models, Time-series analysis -- Forecasting -- Mathematical models, Fourier transformations | ||||||||
| Journal or Publication Title: | IEEE Transactions on Knowledge and Data Engineering | ||||||||
| Publisher: | IEEE Computer Society | ||||||||
| ISSN: | 1041-4347 | ||||||||
| Official Date: | 1 December 2018 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 8 May 2018 | ||||||||
| Volume: | 30 | ||||||||
| Number: | 12 | ||||||||
| Page Range: | 2298 -2311 | ||||||||
| DOI: | 10.1109/TKDE.2018.2820119 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| RIOXX Funder/Project Grant: |
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