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| Field |
Value |
| Title: | Mining Temporal Co-orientation Pattern from Spatio-temporal Databases |
| Authors: | Shan, Man-kwan;Wei, Ling-yin
沈錳坤 |
| Contributors: | 資科系 |
| Date: | 2007 |
| Issue Date: | 2015-06-17 15:44:48 (UTC+8) |
| Abstract: | A spatial co-orientation pattern refers to objects that frequently occur with the same spatial orientation, e.g. left, right, below, etc., among images. In this paper, we introduce temporal co-orientation pattern mining which is the problem of temporal aspects of spatial co-orientation patterns. A temporal co- orientation pattern represents how spatial co-orientation patterns change over time. Temporal co-orientation pattern mining is useful for discovering tactics from play sequences of sports video data, because the most tactic patterns of basketball competition are constituted of such spatial co-orientation patterns in time order. We propose the three-stage approach, which transforms the problem into sequential pattern mining, for mining temporal co-orientation patterns. We experimentally evaluate the performance of the proposed algorithm and analysis the effect of these stages. |
| Relation: | Pacific-Asia Conference on Knowledge Discovery and Data Mining - PAKDD , pp. 895-903 |
| Data Type: | article |
| DOI: | http://dx.doi.org/10.1007/978-3-540-71701-0_100 |
| DCField |
Value |
Language |
| dc.contributor (Contributor) | 資科系 | |
| dc.creator (Authors) | Shan, Man-kwan;Wei, Ling-yin | |
| dc.creator (Authors) | 沈錳坤 | zh_TW |
| dc.date (Date) | 2007 | |
| dc.date.accessioned | 2015-06-17 15:44:48 (UTC+8) | - |
| dc.date.available | 2015-06-17 15:44:48 (UTC+8) | - |
| dc.date.issued (Issue Date) | 2015-06-17 15:44:48 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/75896 | - |
| dc.description.abstract (Abstract) | A spatial co-orientation pattern refers to objects that frequently occur with the same spatial orientation, e.g. left, right, below, etc., among images. In this paper, we introduce temporal co-orientation pattern mining which is the problem of temporal aspects of spatial co-orientation patterns. A temporal co- orientation pattern represents how spatial co-orientation patterns change over time. Temporal co-orientation pattern mining is useful for discovering tactics from play sequences of sports video data, because the most tactic patterns of basketball competition are constituted of such spatial co-orientation patterns in time order. We propose the three-stage approach, which transforms the problem into sequential pattern mining, for mining temporal co-orientation patterns. We experimentally evaluate the performance of the proposed algorithm and analysis the effect of these stages. | |
| dc.format.extent | 128 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (Relation) | Pacific-Asia Conference on Knowledge Discovery and Data Mining - PAKDD , pp. 895-903 | |
| dc.title (Title) | Mining Temporal Co-orientation Pattern from Spatio-temporal Databases | |
| dc.type (Data Type) | article | en |
| dc.identifier.doi (DOI) | 10.1007/978-3-540-71701-0_100 | |
| dc.doi.uri | http://dx.doi.org/10.1007/978-3-540-71701-0_100 | |
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