A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data
A large amount of time series data is being generated every day in a wide range of sensor application domains. The symbolic aggregate approximation (SAX) is a well-known time series representation method, which has a lower bound to Euclidean distance and may discretize continuous time series. SAX ha...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/13/11/284 |
| _version_ | 1827702627759030272 |
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| author | Zhenwen He Shirong Long Xiaogang Ma Hong Zhao |
| author_facet | Zhenwen He Shirong Long Xiaogang Ma Hong Zhao |
| author_sort | Zhenwen He |
| collection | DOAJ |
| description | A large amount of time series data is being generated every day in a wide range of sensor application domains. The symbolic aggregate approximation (SAX) is a well-known time series representation method, which has a lower bound to Euclidean distance and may discretize continuous time series. SAX has been widely used for applications in various domains, such as mobile data management, financial investment, and shape discovery. However, the SAX representation has a limitation: Symbols are mapped from the average values of segments, but SAX does not consider the boundary distance in the segments. Different segments with similar average values may be mapped to the same symbols, and the SAX distance between them is 0. In this paper, we propose a novel representation named SAX-BD (boundary distance) by integrating the SAX distance with a weighted boundary distance. The experimental results show that SAX-BD significantly outperforms the SAX representation, ESAX representation, and SAX-TD representation. |
| first_indexed | 2024-03-10T14:59:55Z |
| format | Article |
| id | doaj.art-899e8d83f76140c186abca16f08d2ef5 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T14:59:55Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-899e8d83f76140c186abca16f08d2ef52023-11-20T20:15:02ZengMDPI AGAlgorithms1999-48932020-11-01131128410.3390/a13110284A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series DataZhenwen He0Shirong Long1Xiaogang Ma2Hong Zhao3School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, ChinaSchool of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, ChinaDepartment of Computer Science, University of Idaho, 875 Perimeter Drive MS 1010, Moscow, ID 83844-1010, USASchool of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, ChinaA large amount of time series data is being generated every day in a wide range of sensor application domains. The symbolic aggregate approximation (SAX) is a well-known time series representation method, which has a lower bound to Euclidean distance and may discretize continuous time series. SAX has been widely used for applications in various domains, such as mobile data management, financial investment, and shape discovery. However, the SAX representation has a limitation: Symbols are mapped from the average values of segments, but SAX does not consider the boundary distance in the segments. Different segments with similar average values may be mapped to the same symbols, and the SAX distance between them is 0. In this paper, we propose a novel representation named SAX-BD (boundary distance) by integrating the SAX distance with a weighted boundary distance. The experimental results show that SAX-BD significantly outperforms the SAX representation, ESAX representation, and SAX-TD representation.https://www.mdpi.com/1999-4893/13/11/284time seriesSAXESAXSAX-TDSAX-BD |
| spellingShingle | Zhenwen He Shirong Long Xiaogang Ma Hong Zhao A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data Algorithms time series SAX ESAX SAX-TD SAX-BD |
| title | A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data |
| title_full | A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data |
| title_fullStr | A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data |
| title_full_unstemmed | A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data |
| title_short | A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data |
| title_sort | boundary distance based symbolic aggregate approximation method for time series data |
| topic | time series SAX ESAX SAX-TD SAX-BD |
| url | https://www.mdpi.com/1999-4893/13/11/284 |
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