PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA
Massive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective in finding clusters, becomes an important clustering approaches in the trajectory data mining. However, the traditional spectral clustering lacks the temporal expansi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-09-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/1173/2017/isprs-archives-XLII-2-W7-1173-2017.pdf |
| _version_ | 1818960302285258752 |
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| author | Y. Z. Gu K. Qin K. Qin Y. X. Chen M. X. Yue T. Guo |
| author_facet | Y. Z. Gu K. Qin K. Qin Y. X. Chen M. X. Yue T. Guo |
| author_sort | Y. Z. Gu |
| collection | DOAJ |
| description | Massive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective
in finding clusters, becomes an important clustering approaches in the trajectory data mining. However, the traditional spectral
clustering lacks the temporal expansion on the algorithm and limited in its applicability to large-scale problems due to its high
computational complexity. This paper presents a parallel spatiotemporal spectral clustering based on multiple acceleration solutions
to make the algorithm more effective and efficient, the performance is proved due to the experiment carried out on the massive taxi
trajectory dataset in Wuhan city, China. |
| first_indexed | 2024-12-20T11:55:22Z |
| format | Article |
| id | doaj.art-4bdb8e8910044349a3895b555e5e6331 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-20T11:55:22Z |
| publishDate | 2017-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-4bdb8e8910044349a3895b555e5e63312022-12-21T19:41:41ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-09-01XLII-2-W71173118010.5194/isprs-archives-XLII-2-W7-1173-2017PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATAY. Z. Gu0K. Qin1K. Qin2Y. X. Chen3M. X. Yue4T. Guo5School of Remote Sensing and Information Engineering, Wuhan University, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, ChinaCollaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, ChinaNanjing University of Posts and Telecommunications, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, ChinaMassive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective in finding clusters, becomes an important clustering approaches in the trajectory data mining. However, the traditional spectral clustering lacks the temporal expansion on the algorithm and limited in its applicability to large-scale problems due to its high computational complexity. This paper presents a parallel spatiotemporal spectral clustering based on multiple acceleration solutions to make the algorithm more effective and efficient, the performance is proved due to the experiment carried out on the massive taxi trajectory dataset in Wuhan city, China.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/1173/2017/isprs-archives-XLII-2-W7-1173-2017.pdf |
| spellingShingle | Y. Z. Gu K. Qin K. Qin Y. X. Chen M. X. Yue T. Guo PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA |
| title_full | PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA |
| title_fullStr | PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA |
| title_full_unstemmed | PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA |
| title_short | PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA |
| title_sort | parallel spatiotemporal spectral clustering with massive trajectory data |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/1173/2017/isprs-archives-XLII-2-W7-1173-2017.pdf |
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