Simple Distances for Trajectories via Landmarks
Author:
Affiliation:
1. School of Computing, University of Utah., Salt Lake City, Utah, USA
Funder
NSF
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3347146.3359098
Reference17 articles.
1. Maria Astefanoaei Paul Cesaretti Panagiota Katsikouli and Mayank Goswami and Rik Sarkar. 2018. Multi-resolution sketches and locality sensitive hashing for fast trajectory processing. In SIGSPATIAL. Maria Astefanoaei Paul Cesaretti Panagiota Katsikouli and Mayank Goswami and Rik Sarkar. 2018. Multi-resolution sketches and locality sensitive hashing for fast trajectory processing. In SIGSPATIAL.
2. Lei Chen M. Tamer Özsu and Vincent Oria. 2005. Robust and fast similarity search for moving object trajectories.. In SIGMOD. Lei Chen M. Tamer Özsu and Vincent Oria. 2005. Robust and fast similarity search for moving object trajectories.. In SIGMOD.
3. Michael O. Cruz Hendrik Macedo R. Barreto and Adolfo Guimaraes. 2016. GPS Trajectories Data Set. https://archive.ics.uci.edu/ml/datasets/GPS+Trajectories Michael O. Cruz Hendrik Macedo R. Barreto and Adolfo Guimaraes. 2016. GPS Trajectories Data Set. https://archive.ics.uci.edu/ml/datasets/GPS+Trajectories
4. Yixiang Fang Reynold Cheng Wenbin Tang Silviu Maniu and Xuan S. Yang:. 2016. Scalable algorithms for nearest-neighbor joins on big trajectory data. In ICDE. Yixiang Fang Reynold Cheng Wenbin Tang Silviu Maniu and Xuan S. Yang:. 2016. Scalable algorithms for nearest-neighbor joins on big trajectory data. In ICDE.
5. Elias Frentzos Kostas Gratsias Nikos Pelekis and Yannis Theodoridis. 2005. Nearest Neighbor Search on Moving Object Trajectories. In SSTD. Elias Frentzos Kostas Gratsias Nikos Pelekis and Yannis Theodoridis. 2005. Nearest Neighbor Search on Moving Object Trajectories. In SSTD.
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