FAQ: Questions Asked Frequently

Mahmoud Abo Khamis, H. Ngo, A. Rudra
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引用次数: 171

Abstract

We define and study the Functional Aggregate Query (FAQ) problem, which encompasses many frequently asked questions in constraint satisfaction, databases, matrix operations, probabilistic graphical models and logic. This is our main conceptual contribution. We then present a simple algorithm called "InsideOut" to solve this general problem. InsideOut is a variation of the traditional dynamic programming approach for constraint programming based on variable elimination. Our variation adds a couple of simple twists to basic variable elimination in order to deal with the generality of FAQ, to take full advantage of Grohe and Marx's fractional edge cover framework, and of the analysis of recent worst-case optimal relational join algorithms. As is the case with constraint programming and graphical model inference, to make InsideOut run efficiently we need to solve an optimization problem to compute an appropriate variable ordering. The main technical contribution of this work is a precise characterization of when a variable ordering is `semantically equivalent' to the variable ordering given by the input FAQ expression. Then, we design an approximation algorithm to find an equivalent variable ordering that has the best `fractional FAQ-width'. Our results imply a host of known and a few new results in graphical model inference, matrix operations, relational joins, and logic. We also briefly explain how recent algorithms on beyond worst-case analysis for joins and those for solving SAT and #SAT can be viewed as variable elimination to solve FAQ over compactly represented input functions.
常见问题:常见问题
本文定义并研究了功能聚合查询(FAQ)问题,该问题涉及约束满足、数据库、矩阵运算、概率图模型和逻辑等方面的常见问题。这是我们在概念上的主要贡献。然后,我们提出一个简单的算法,称为“InsideOut”来解决这个一般问题。InsideOut是基于变量消去的约束规划的传统动态规划方法的一种变体。为了处理常见问题的通用性,为了充分利用Grohe和Marx的分数边缘覆盖框架,以及对最近的最坏情况最优关系连接算法的分析,我们的变体在基本变量消除中添加了一些简单的变化。与约束编程和图形模型推理的情况一样,为了使InsideOut有效运行,我们需要解决一个优化问题来计算适当的变量排序。这项工作的主要技术贡献是精确描述变量排序何时与输入FAQ表达式给出的变量排序“语义等价”。然后,我们设计了一种近似算法来寻找具有最佳“分数faq宽度”的等效变量排序。我们的结果暗示了图形模型推理、矩阵操作、关系连接和逻辑方面的许多已知结果和一些新的结果。我们还简要解释了最近关于超越最坏情况分析的连接算法以及用于解决SAT和#SAT的算法如何被视为变量消除,以解决紧凑表示的输入函数上的常见问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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