Optimizing Video Selection LIMIT Queries With Commonsense Knowledge
Summary: Introduces Paine: a cheap, lossy-index plus probabilistic commonsense models that patch missed targets and prioritize predicate-related videos for LIMIT video-selection queries. Cuts expensive detector scans dramatically—up to 97.8% fewer videos; even zero-content commonsense models give ~75% improvement while keeping index construction costs low. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wenjia He
- 2. Ibrahim Sabek
- 3. Yuze Lou
- 4. Michael Cafarella
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,394 | MAST: Towards Efficient Analytical Query Processing on Point Cloud Data | 2025 | SIGMOD | 4.1905499e-05 |
| 10,481 | Approximating Opaque Top-k Queries | 2025 | SIGMOD | 4.1905499e-05 |
| 10,532 | Scalable Complex Event Processing on Video Streams | 2025 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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