[1] |
SCHUESSLER N , AXHAUSEN K . Processing raw data from global positioning systems without additional information[J]. Transportation Research Record:Journal of the Transportation Research Board, 2009(2105): 28-36.
|
[2] |
DOUGLAS D H , PEUCKER T K . Algorithms for the reduction of the number of points required to represent a digitized line or its caricature[J]. Cartographica:The International Journal for Geographic Information and Geovisualization, 1973,10(2): 112-122.
|
[3] |
MERATNIA N , ROLF A . Spatiotemporal compression techniques for moving point objects[A]. Advances in Database Technology-EDBT[C]. 2004. 765-782.
|
[4] |
ZHENG Y , et al . Mining interesting locations and travel sequences from GPS trajectories[A]. Proceedings of the 18th International Conference on World Wide Web[C]. 2009.
|
[5] |
PALMA A T , et al . A clustering-based approach for discovering interesting places in trajectories[A]. Proceedings of the 2008 ACM Symposium on Applied Computing[C]. 2008.
|
[6] |
GREENFELD J S . Matching GPS observations to locations on a digital map[A]. Transportation Research Board 81st Annual Meeting[C]. 2002.
|
[7] |
BRAKATSOULAS S ,et al. On map-matching vehicle tracking data[A]. Proceedings of the 31st International Conference on Very Large Data Bases[C]. 2005.
|
[8] |
NEWSON P , KRUMM J . Hidden Markov map matching through noise and sparseness[A]. Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems[C]. 2009.
|
[9] |
LIU K , et al . Effective map-matching on the most simplified road network[A]. Proceedings of the 20th International Conference on Advances in Geographic Information Systems[C]. 2012ACM.
|
[10] |
LI S ,et al. Quick geo-fencing using trajectory partitioning and boundary simplification[A]. Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems[C]. 2013.
|
[11] |
TANG Y , ZHU A D , XIAO X . An efficient algorithm for mapping vehicle trajectories onto road networks[A]. Proceedings of the 20th International Conference on Advances in Geographic Information Systems[C]. 2012.
|
[12] |
ZHENG K ,et al. Reducing uncertainty of low-sampling-rate trajectories[A]. Data Engineering (ICDE),2012 IEEE 28th International Conference on[C]. 2012.
|
[13] |
SU H ,et al. Calibrating trajectory data for similarity-based analysis[A]. Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data[C]. 2013.
|
[14] |
SU H ,et al. Calibrating trajectory data for spatio-temporal similarity analysis[J]. The VLDB Journal, 2015,24(1): 93-116.
|
[15] |
SISTLA A P ,et al. Modeling and querying moving objects[A]. ICDE[C]. 1997.
|
[16] |
GüTING R H ,et al. A foundation for representing and querying moving objects[J]. ACM Transactions on Database Systems (TODS), 2000,25(1): 1-42.
|
[17] |
WANG H ,et al. SharkDB:An in-memory column-oriented trajectory storage[A]. Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management[C]. 2014.
|
[18] |
KELLARIS PELEKIS G N , THEODORIDIS Y . Trajectory compression under network constraints[A]. Advances in Spatial and Temporal Databases[C]. 2009. 392-398.
|
[19] |
SONG R ,et al. PRESS:A novel framework of trajectory compression in road networks[J]. Proceedings of the VLDB Endowment, 2014,7(9): 661-672.
|
[20] |
CHAN W S , CHIN F . Approximation of polygonal curves with minimum number of line segments or minimum error[J]. International Journal of Computational Geometry & Applications, 1996,6(1): 59-77.
|
[21] |
GUTTMAN A . R-trees:a dynamic index structure for spatial searching[A]. SIGMOD[C]. 1984. 47-57.
|
[22] |
PFOSER D , JENSEN C S , THEODORIDIS Y . Novel approaches to the indexing of moving object trajectories[A]. Proceedings of VLDB[C]. 2000.
|
[23] |
NASCIMENTO M A , SILVA J R . Towards historical R-trees[A]. Proceedings of the 1998 ACM Symposium on Applied Computing[C]. 1998.
|
[24] |
YUFEI T , PAPADIAS D . MV3R-tree:a spatio-temporal access method for timestamp and interval queries[A]. VLDB[C]. 2001. 431-440.
|
[25] |
CHAKKA V P , EVERSPAUGH A C , PATEL J M . Indexing large trajectory data sets with SETI[A]. CIDR[C]. 2003.
|
[26] |
丁治明 . 一种适合于频繁位置更新的网络受限移动对象轨迹索引[J]. 计算机学报, 2012,35(7): 1448-1461. DING Z M . An index structure for frequently updated network-constrainted moving object trajectories[J]. Chinese Journal of Computers, 2012,35(7): 1448-1461.
|
[27] |
VLACHOS M , KOLLIOS G , GUNOPULOS D . Discovering similar multidimensional trajectories[A]. Data Engineering,2002 Proceedings 18th International Conference on[C]. 2002.
|
[28] |
CHEN L , NG R . On the marriage of lp-norms and edit distance[A]. Proceedings of the Thirtieth International Conference on Very Large Data Bases-Volume[C]. 2004.
|
[29] |
CHEN L , ?ZSU M T , ORIA V . Robust and fast similarity search for moving object trajectories[A]. Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data[C]. 2005.ACM.
|
[30] |
CHEN Z , et al . Searching trajectories by locations:an efficiency study[A]. Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data[C]. 2010.
|
[31] |
ZHENG Y , et al . Learning transportation mode from raw gps data for geographic applications on the web[A]. Proceedings of the 17th International Conference on World Wide Web[C]. 2008.
|
[32] |
YAN Z , et al . Semantic trajectories:Mobility data computation and annotation[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2013,4(3): 49.
|
[33] |
ALVARES L O , et al . A model for enriching trajectories with semantic geographical information[A]. Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems[C]. 2007.
|
[34] |
ZHENG K , et al . Towards efficient search for activity trajectories[A]. Data Engineering (ICDE),2013 IEEE 29th International Conference[C]. 2013.
|
[35] |
LIN B , SU J . One way distance:For shape based similarity search of moving object trajectories[J]. Geoinformatica, 2008,12(2): 117-142.
|
[36] |
ZHENG B , et al . Approximate keyword search in semantic trajectory database[A]. Data Engineering (ICDE),2015 IEEE 31st International Conference[C]. 2015.
|
[37] |
MA C , et al . KSQ:Top-k similarity query on uncertain trajectories[J]. Knowledge and Data Engineering,IEEE Transactions, 2013,25(9): 2049-2062.
|
[38] |
ZHENG Y . Trajectory data mining:an overview[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2015,6(3): 29.
|
[39] |
GIANNOTTI F ,et al. Trajectory pattern mining[A]. Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining[C]. 2007.
|
[40] |
WANG Y , ZHENG Y , XUE Y . Travel time estimation of a path using sparse trajectories[A]. Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining[C]. 2014.
|
[41] |
CHEN Z , SHEN H T , ZHOU X . Discovering popular routes from trajectories[A]. Data Engineering (ICDE),2011 IEEE 27th International Conference[C]. 2011.
|
[42] |
LEE J G , HAN J , LI X . Trajectory outlier detection:A partition-and-detect framework[A]. Data Engineering,ICDE 2008 IEEE 24th International Conference[C]. 2008.
|
[43] |
KRUMM J , HORVITZ E . Predestination:Inferring destinations from partial trajectories[A]. UbiComp 2006:Ubiquitous Computing[C]. 2006. 243-260.
|
[44] |
LIAO L , et al . Learning and inferring transportation routines[J]. Artificial Intelligence, 2007,171(5): 311-331.
|
[45] |
CAO H , MAMOULIS N , CHEUNG D W . Discovery of periodic patterns in spatiotemporal sequences[J]. Knowledge and Data Engineering,IEEE Transactions on, 2007,19(4): 453-467.
|
[46] |
GUDMUNDSSON J , KREVELD M V . Computing longest duration flocks in trajectory data[A]. Proceedings of the 14th Annual ACM International Symposium on Advances in Geographic Information Systems[C]. 2006.ACM.
|
[47] |
JEUNG H , et al . Discovery of convoys in trajectory databases[J]. Proceedings of the VLDB Endowment, 2008,1(1): 1068-1080.
|
[48] |
LI Z , et al . Swarm:Mining relaxed temporal moving object clusters[J]. Proceedings of the VLDB Endowment, 2010,3(1-2): 723-734.
|
[49] |
ZHENG K , ZHENG Y ,et al. On discovery of gathering patterns from trajectories[A]. ICDE[C]. 2013. 242-253
|
[50] |
ZHENG K , ZHENG Y ,et al. Online discovery of gathering patterns over trajectories[J]. IEEE Trans Knowl Data Eng, 2004 26(8): 1974-1988.
|
[51] |
TANG L A , et al . On discovery of traveling companions from streaming trajectories[A]. Data Engineering (ICDE),IEEE 28th International Conference[C]. 2012.
|
[52] |
LEE J G , HAN J , WHANG K Y . Trajectory clustering:a partition-and-group framework[A]. Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data[C]. 2007.
|
[53] |
LI Z , et al . Incremental clustering for trajectories[A]. Database Systems for Advanced Applications[C]. 2010.
|
[54] |
CAO X , CONG G , JENSEN C S . Mining significant semantic locations from GPS data[J]. Proceedings of the VLDB Endowment, 2010,3(1-2): 1009-1020.
|
[55] |
YUAN J , et al . T-drive:driving directions based on taxi trajectories[A]. Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems[C]. 2010.
|
[56] |
SU H , et al . Making sense of trajectory data:a partition-and- summarization approach[A]. Data Engineering (ICDE),IEEE 31st International Conference[C]. 2015.
|