Query Repairs

2025-01-19

AI Summary

This paper addresses the problem of repairing conjunctive queries (CQs) using user-provided positive and negative examples, aiming to generate semantically nearby and efficient corrected queries. Methodologically, it unifies query containment and CQ distance into a single formal notion of proximity—a preordering—thereby establishing the first rigorous, semantics-based repair framework for CQs. It systematically analyzes the existence, uniqueness, and computational complexity boundaries of repairs under various preorderings. By integrating query implication theory, CQ distance metrics, and formal semantic preorderings, the paper proposes a decidable algorithmic paradigm for query repair. The results provide both a solid theoretical foundation and practical, implementable algorithms for interactive query debugging and correction.

Technology Category

• Data Mining & Knowledge Management: Intelligent Query Processing
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

Abstract

We formalize and study the problem of repairing database queries based on user feedback in the form of a collection of labeled examples. We propose a framework based on the notion of a proximity pre-order, and we investigate and compare query repairs for conjunctive queries (CQs) using different such pre-orders. The proximity pre-orders we consider are based on query containment and on distance metrics for CQs.

Problem

• Database Query Correction
• Example-based Learning
• Query Efficiency

Innovation

• Proximity Pre-ranking
• Database Query Correction
• Query Containment and Distance