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Researchers explore ASP(Q) for inconsistent prioritized data querying

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method using answer set programming with quantifiers (ASP(Q)) to manage inconsistent prioritized data. This approach defines three types of optimal repairs—Pareto-, globally-, and completion-optimal—to handle conflicting facts based on their priority. The paper introduces the first implementation of globally-optimal repair-based semantics and a tractable under-approximation called grounded semantics, with experimental results demonstrating their feasibility and impact. AI

IMPACT Introduces novel computational techniques for data inconsistency resolution, potentially impacting knowledge representation and reasoning systems.

RANK_REASON This is a research paper detailing a new computational method for handling inconsistent data.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Researchers explore ASP(Q) for inconsistent prioritized data querying

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This is a research paper detailing a new computational method for handling inconsistent data.
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Giuseppe Mazzotta ·

    Using ASP(Q) to Handle Inconsistent Prioritized Data

    We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data, where a priority relation between conflicting facts is exploited to define three notions of optimal repairs (Pareto-, globally- …

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