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- Publisher Website: 10.1109/CISE.2010.5677000
- Scopus: eid_2-s2.0-79951622608
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Conference Paper: Mining frequent trajectory patterns from GPS tracks
Title | Mining frequent trajectory patterns from GPS tracks |
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Authors | |
Keywords | Sptiotemporal data Clustering Frequent trajectory patterns Graph-based searching Trajectory database |
Issue Date | 2010 |
Publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1003013 |
Citation | The 2010 International Conference on Computational Intelligence and Software Engineering (CiSE 2010), Wuhan, China, 10-12 December 2010. In Proceedings of CiSE, 2010, p. 1-6 How to Cite? |
Abstract | As recent advances and wide usage of mobile devices with positioning capabilities, trajectory database that captures the historical movements of populations of moving objects becomes important. Given such a database that contains many taxi trajectories, we study a new problem of discovering frequent sequential patterns. The proposed method comprises two phases. First, we cluster the stay points of taxis to get collocation patterns for passengers. Then, for each pattern instance, we use an efficient graph-based searching algorithm to mine the frequent trajectory patterns, which utilizes the adjacency property to reduce the search space. The performance evaluation demonstrates that our method outperforms the Apriori-based and PrefixSpan-based methods. ©2010 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/140002 |
ISBN | |
References |
DC Field | Value | Language |
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dc.contributor.author | Chen, G | en_HK |
dc.contributor.author | Chen, B | en_HK |
dc.contributor.author | Yu, Y | en_HK |
dc.date.accessioned | 2011-09-23T06:04:34Z | - |
dc.date.available | 2011-09-23T06:04:34Z | - |
dc.date.issued | 2010 | en_HK |
dc.identifier.citation | The 2010 International Conference on Computational Intelligence and Software Engineering (CiSE 2010), Wuhan, China, 10-12 December 2010. In Proceedings of CiSE, 2010, p. 1-6 | en_HK |
dc.identifier.isbn | 978-1-4244-5392-4 | - |
dc.identifier.uri | http://hdl.handle.net/10722/140002 | - |
dc.description.abstract | As recent advances and wide usage of mobile devices with positioning capabilities, trajectory database that captures the historical movements of populations of moving objects becomes important. Given such a database that contains many taxi trajectories, we study a new problem of discovering frequent sequential patterns. The proposed method comprises two phases. First, we cluster the stay points of taxis to get collocation patterns for passengers. Then, for each pattern instance, we use an efficient graph-based searching algorithm to mine the frequent trajectory patterns, which utilizes the adjacency property to reduce the search space. The performance evaluation demonstrates that our method outperforms the Apriori-based and PrefixSpan-based methods. ©2010 IEEE. | en_HK |
dc.language | eng | en_US |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1003013 | - |
dc.relation.ispartof | International Conference on Computational Intelligence and Software Engineering Proceedings | en_HK |
dc.rights | ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | Sptiotemporal data | en_HK |
dc.subject | Clustering | en_HK |
dc.subject | Frequent trajectory patterns | en_HK |
dc.subject | Graph-based searching | en_HK |
dc.subject | Trajectory database | - |
dc.title | Mining frequent trajectory patterns from GPS tracks | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Chen, G: zjucg@zju.edu.cn | en_HK |
dc.identifier.email | Chen, B: baoquan.chen@gmail.com | - |
dc.identifier.email | Yu, Y: yzyu@cs.hku.hk | - |
dc.identifier.authority | Yu, Y=rp01415 | en_HK |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/CISE.2010.5677000 | en_HK |
dc.identifier.scopus | eid_2-s2.0-79951622608 | en_HK |
dc.identifier.hkuros | 194324 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-79951622608&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 6 | - |
dc.publisher.place | United States | - |
dc.description.other | The 2010 International Conference on Computational Intelligence and Software Engineering (CiSE 2010), Wuhan, China, 10-12 December 2010. In Proceedings of CiSE, 2010, p. 1-6 | - |
dc.identifier.scopusauthorid | Yu, Y=8554163500 | en_HK |
dc.identifier.scopusauthorid | Chen, B=36974946000 | en_HK |
dc.identifier.scopusauthorid | Chen, G=35336243800 | en_HK |