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A General Framework for Modeling and Processing Optimization Queries

Summary: Proposes a general framework of model-based optimization queries using a generic model to specify objectives and attribute constraints. For convex objectives/constraints, it maps to convex programs and offers an I/O-efficient, unified processing framework with near-specialized performance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9516
Venue
VLDB
Year
2007
Pagerank
4.4278238e-05
Overall Rank
8,889 | 38.17%
DOI
-

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Rank Citing Paper Year Venue Pagerank
7,787 Jigsaw: Efficient Optimization Over Uncertain Enterprise Data 2011 SIGMOD 4.6512526e-05
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