arXiv:2503.22358cs.DBcs.AI2025-03被引 10

提出可高效计算的数据库责任度量方法,解决传统方法难算问题

Shapley Revisited: Tractable Responsibility Measures for Query Answers

  • 基于最小支撑加权和定义新责任度量,逻辑清晰易实现
  • 对多数查询类型计算复杂度为可 tractable,包括并集的连结查询
  • 既保持合理性质又避免原方法#P难问题,适合实际数据库应用

Shapley值源自合作博弈论,被用于量化数据库事实对查询结果的贡献程度。对于非数值型查询,通过将事实视为玩家、以子集是否满足查询作为收益函数(0或1)来建模。尽管概念简单,但其计算在数据复杂性上属于#P难,即使对简单的连结查询也如此。为此,本文重新审视合理责任度量的标准,提出一类新的度量——最小支撑加权和(WSMS),满足直观合理性。有趣的是,尽管其定义形式与Shapley值无明显关联,我们证明每个WSMS度量等价于某个特定合作博弈下的Shapley值。更重要的是,该度量对一大类查询(包括所有并集的连结查询)具有可处理的数据复杂度。此外,我们还分析了其组合复杂度,给出了各类连结查询子类的可计算性结论。

原文摘要 · Abstract (English)

The Shapley value, originating from cooperative game theory, has been employed to define responsibility measures that quantify the contributions of database facts to obtaining a given query answer. For non-numeric queries, this is done by considering a cooperative game whose players are the facts and whose wealth function assigns 1 or 0 to each subset of the database, depending on whether the query answer holds in the given subset. While conceptually simple, this approach suffers from a notable drawback: the problem of computing such Shapley values is #P-hard in data complexity, even for simple conjunctive queries. This motivates us to revisit the question of what constitutes a reasonable responsibility measure and to introduce a new family of responsibility measures -- weighted sums of minimal supports (WSMS) -- which satisfy intuitive properties. Interestingly, while the definition of WSMSs is simple and bears no obvious resemblance to the Shapley value formula, we prove that every WSMS measure can be equivalently seen as the Shapley value of a suitably defined cooperative game. Moreover, WSMS measures enjoy tractable data complexity for a large class of queries, including all unions of conjunctive queries. We further explore the combined complexity of WSMS computation and establish (in)tractability results for various subclasses of conjunctive queries.

数据库责任度量算法复杂度博弈论

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