Processing Moving kNN Queries Using Influential Neighbor Sets
Summary: Proposes Influential Neighbor Sets as safe guarding objects to maintain moving kNNs without costly safe region updates. Proves that when current kNNs are closer than safeguarding objects, they stay valid, and that this region is maximal, reducing recomputations; validated by extensive experiments against state-of-the-art on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chuanwen Li
- 2. Yu Gu
- 3. Jianzhong Qi
- 4. Ge Yu
- 5. Rui Zhang
- 6. Wang Yi
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,207 | Closest Pairs Search Over Data Stream | 2023 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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