用ASP(Q)处理有优先级的数据不一致问题，实现更可靠的查询修复。
Using ASP(Q) to Handle Inconsistent Prioritized Data
- 基于优先级冲突事实，定义三种最优修复方式
- 首次实现全局最优修复语义和可计算的近似语义
- 实验验证了不同修复策略在实际中的可行性
本文探讨使用答案集编程（ASP）及其带量词扩展（ASP(Q)）来处理具有优先级的不一致数据查询问题。通过利用冲突事实间的优先关系，定义了三种最优修复概念：帕累托最优、全局最优与完成最优。研究考虑了三种经典语义（AR、勇敢、IAR）在这些最优修复下的变体，其查询回答在一大类逻辑理论中位于多项式层级的第一或第二层。特别地，本文首次实现了基于全局最优修复的语义，以及首个可计算的基底语义——该语义是所有最优修复语义的可处理下界近似。实验评估揭示了在全局最优修复语义下计算答案的可行性，以及采用不同语义、近似方法和编码方式的影响。
原文摘要 · Abstract (English)
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- and completion-optimal). We consider the variants of three well-known semantics (AR, brave and IAR) that use these optimal repairs, and for which query answering is in the first or second level of the polynomial hierarchy for a large class of logical theories. Notably, this paper presents the first implementation of globally-optimal repair-based semantics, as well as the first implementation of the grounded semantics, which is a tractable under-approximation of all these optimal repair-based semantics. Our experimental evaluation sheds light on the feasibility of computing answers under globally-optimal repair semantics and the impact of adopting different semantics, approximations, and encodings.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。