Database Paper Browser

Back to papers

Accelerating Aggregation Queries on Unstructured Streams of Data

Summary: InQuest: streaming, multimodal aggregation over unstructured data using cheap proxy models plus sampling to limit expensive oracle invocations, producing real-time approximate query answers with statistical guarantees. Theory: expected error on stationary streams decays ∝1/(oracle budget); evaluation: matches streaming baselines with up to 5× fewer oracle calls and improves RMSE vs a state-of-the-art batch method. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13131
Venue
VLDB
Year
2023
Pagerank
4.613455e-05
Overall Rank
7,928 | 44.85%
DOI
10.14778/3611479.3611496

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 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