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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)

Paper ID
124
Venue
CIDR
Year
2009
Pagerank
5.5769911e-05
Overall Rank
7,635 | 47.62%
DOI
-

Incoming Non-self Citations Over Time

Authors

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
6,201 Generating Preview Tables for Entity Graphs 2016 SIGMOD 5.9455064e-05
6,627 Schema-free SQL 2014 SIGMOD 5.8198662e-05
12,385 Keyword Search on Form Results 2011 VLDB 5.093636e-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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