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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Clustering multidimensional sequences in spatial and temporal databases |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Knowledge and Information Systems (KAIS) |
| Publisher | Springer |
| Geographical Reach | international |
| ISSN | 0219-3116 |
| Volume | 16 |
| Number | 1 |
| Page Range | 29 - 51 |
| Date | 2008 |
| Abstract Text | Many environmental, scientific, technical or medical database applications require effective and efficient mining of time series, sequences or trajectories of measurements taken at different time points and positions forming large temporal or spatial databases. Particularly the analysis of concurrent andmultidimensional sequences poses newchallenges in finding clusters of arbitrary length and varying number of attributes. We present a novel algorithm capable of finding parallel clusters in different subspaces and demonstrate our results for temporal and spatial applications. Our analysis of structural quality parameters in rivers is successfully used by hydrologists to develop measures for river quality improvements. |
| Digital Object Identifier | 10.1007/s10115-007-0121-3 |
| Other Identification Number | merlin-id:304 |
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