Qunits: queried units for database search
Summary: Introduce qunits—independent queried units representing canonical query results, decoupling declarative DB predicate semantics from presentation/aggregation. Keyword search is executed over a corpus of qunits treated as IR documents, enabling standard ranking models instead of ad-hoc DB ranking; prototype validates feasibility. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Arnab Nandi (University of Michigan)
- 2. H.V. Jagadish (University of Michigan)
BibTeX Citation
@inproceedings{nandi_cidr09,
address = {Amsterdam, Netherlands},
series = {{CIDR} '09},
title = {{Qunits: queried units for database search}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Nandi, Arnab and Jagadish, H.V.},
year = {2009}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,331 | Generating Preview Tables for Entity Graphs | 2016 | SIGMOD | 5.8121052e-05 |
| 6,724 | Schema-free SQL | 2014 | SIGMOD | 5.6950798e-05 |
| 12,676 | Keyword Search on Form Results | 2011 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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