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
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Authors
- 1. Zeyuan Shang
- 2. Guoliang Li
- 3. Zhifeng Bao
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,610 | IMO: A Toolbox for Simulating and Querying "Infected" Moving Objects | 2020 | VLDB | 4.1905499e-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 |
|---|---|---|---|---|
| 251 | Robust and Fast Similarity Search for Moving Object Trajectories | 2005 | SIGMOD | 0.00030589775 |
| 358 | On The Marriage of Lp-norms and Edit Distance | 2004 | VLDB | 0.00026059337 |
| 2,198 | DITA: Distributed In-Memory Trajectory Analytics | 2018 | SIGMOD | 9.3096071e-05 |
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