DBScholar

Back to papers

Detecting Attribute Dependencies from Query Feedback

Summary: Finds dependent attribute pairs from query feedback without combinatorial search, combining sparse contingency-table evidence via a robust chi-squared variant. Ranks dependencies to retain the most valuable multivariate statistics under catalog budgets, remaining stable with few feedback records. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9824
Venue
VLDB
Year
2007
Pagerank
5.238674e-05
Overall Rank
9,671 | 33.65%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{haas_vldb07,
        title = {{Detecting Attribute Dependencies from Query Feedback}},
        author = {Haas, Peter J. and Hueske, Fabian and Markl, Volker},
        journal = {PVLDB},
        series = {{VLDB} '07},
        pages = {830--841},
        year = {2007}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
6,688 ROX: Run-time Optimization of XQueries 2009 SIGMOD 5.8015211e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 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