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Researchers analyze query relevance complexity in databases

Researchers have analyzed the computational complexity of determining fact relevance to database queries. They found that the problem is generally harder than query evaluation, with NP-hardness arising even in simpler query structures. The study identifies self-joins as a key factor contributing to this difficulty and proposes that limiting self-joins can reduce the complexity to that of query evaluation. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

IMPACT Identifies specific query structures that complicate relevance determination, potentially guiding future database optimization and AI-driven data analysis.

RANK_REASON Academic paper analyzing computational complexity of a database problem.

Read on arXiv cs.AI →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 · Meghyn Bienvenu, Diego Figueira, Pierre Lafourcade ·

    How Hard is it to Decide if a Fact is Relevant to a Query?

    arXiv:2604.22422v1 Announce Type: cross Abstract: We consider the following fundamental problem: given a database D, Boolean conjunctive query (CQ) q, and fact f in D, decide whether f is relevant to q wrt. D, i.e., does f belong to a minimal subset S of D such that S |= q. Despi…

  2. arXiv cs.AI TIER_1 · Pierre Lafourcade ·

    How Hard is it to Decide if a Fact is Relevant to a Query?

    We consider the following fundamental problem: given a database D, Boolean conjunctive query (CQ) q, and fact f in D, decide whether f is relevant to q wrt. D, i.e., does f belong to a minimal subset S of D such that S |= q. Despite being of central importance to query answer exp…