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PDQ: Proof-driven Query Answering over Web-based Data

Summary: PDQ introduces proof-driven query planning over Web-based sources, generating plans from proofs that a query is answerable. Constraint-, access-, and cost-aware, it rewrites expensive queries via source relations, respects access restrictions, and selects low-cost plans from known costs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10817
Venue
VLDB
Year
2014
Pagerank
4.5486275e-05
Overall Rank
8,259 | 42.55%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
2,936 Querying with Access Patterns and Integrity Constraints 2015 VLDB 7.8554347e-05
3,004 Benchmarking the Chase 2017 PODS 7.7314538e-05
9,377 Exploiting the Power of Equality-generating Dependencies in Ontological Reasoning 2022 VLDB 4.347117e-05
9,714 Materializing Knowledge Bases via Trigger Graphs 2021 VLDB 4.299267e-05
10,908 Chase Termination Beyond Polynomial Time 2024 PODS 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
870 Query Optimization in the Presence of Limited Access Patterns 1999 SIGMOD 0.00015771912
2,100 Query Optimization over Web Services 2006 VLDB 9.5443207e-05
5,181 Active Knowledge: Dynamically Enriching RDF Knowledge Bases by Web Services 2010 SIGMOD 5.6410659e-05
7,626 Generating Low-cost Plans From Proofs 2014 PODS 4.6931334e-05
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