DBScholar

Back to papers

Subtrajectory Clustering: Models and Algorithms

Summary: Introduces pathlet-based clustering of trajectory subsequences, modeling trajectories as concatenations with gaps and noise. Establishes NP-hardness and develops efficient approximation algorithms, including faster methods for well-behaved trajectories. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
1751
Venue
PODS
Year
2018
Pagerank
6.5016379e-05
Overall Rank
4,803 | 67.05%
DOI
10.1145/3196959.3196972

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{agarwal_pods18,
        address = {New York, NY, USA},
        series = {{PODS} '18},
        title = {{Subtrajectory Clustering: Models and Algorithms}},
        url = {https://dl.acm.org/doi/10.1145/3196959.3196972},
        doi = {10.1145/3196959.3196972},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Agarwal, Pankaj K. and Fox, Kyle and Munagala, Kamesh and Nath, Abhinandan and Pan, Jiangwei and Taylor, Erin},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers