DITA: A Distributed In-Memory Trajectory Analytics System
Summary: DITA is an in-memory distributed trajectory analytics system offering threshold-based and KNN similarity search and space-time range queries. It integrates Spark SQL/DataFrame, supports diverse similarity functions, and uses partitioning with global/local indexes plus a filter-verification framework for scalable search and join. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Zeyuan Shang (Brown University)
- 2. Guoliang Li (Tsinghua University)
- 3. Zhifeng Bao (Royal Melbourne Institute of Technology)
BibTeX Citation
@inproceedings{shang_sigmod18,
title = {{DITA: A Distributed In-Memory Trajectory Analytics System}},
author = {Shang, Zeyuan and Li, Guoliang and Bao, Zhifeng},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3193553},
url = {https://dl.acm.org/doi/10.1145/3183713.3193553},
year = {2018}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,801 | IMO: A Toolbox for Simulating and Querying “Infected” Moving Objects | 2020 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 221 | Robust and Fast Similarity Search for Moving Object Trajectories | 2005 | SIGMOD | 0.00024224879 |
| 303 | On The Marriage of Lp-norms and Edit Distance | 2004 | VLDB | 0.00021956234 |
| 2,416 | DITA: Distributed In-Memory Trajectory Analytics | 2018 | SIGMOD | 8.6068712e-05 |
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