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A new rational algorithm for view updating in relational databases

机译:关系数据库中视图更新的一种新的有理算法

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摘要

The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. In order to apply the rationality result of belief dynamics theory to various practical problems, it should be generalized in two respects: first it should allow a certain part of belief to be declared as immutable; and second, the belief state need not be deductively closed. Such a generalization of belief dynamics, referred to as base dynamics, is presented in this paper, along with the concept of a generalized revision algorithm for knowledge bases (Horn or Horn logic with stratified negation). We show that knowledge base dynamics has an interesting connection with kernel change via hitting set and abduction. In this paper, we show how techniques from disjunctive logic programming can be used for efficient (deductive) database updates. The key idea is to transform the given database together with the update request into a disjunctive (datalog) logic program and apply disjunctive techniques (such as minimal model reasoning) to solve the original update problem. The approach extends and integrates standard techniques for efficient query answering and integrity checking. The generation of a hitting set is carried out through a hyper tableaux calculus and magic set that is focused on the goal of minimality.
机译:信念和知识的动态是任何自治系统的主要组成部分之一,该系统应该能够合并新的信息。为了将信念动力学理论的合理性结果应用到各种实际问题中,应该从两个方面进行概括:首先,它应允许信念的某一部分被宣布为不变的;第二,信念状态不需要演绎地封闭。本文介绍了这种信念动力学的一般化,称为基础动力学,以及知识库的广义修正算法(带分层否定的角或角逻辑)的广义修正算法的概念。我们表明,知识库动态通过命中集和诱拐与内核更改有着有趣的联系。在本文中,我们展示了析取逻辑编程中的技术如何用于有效(演绎)数据库更新。关键思想是将给定的数据库与更新请求一起转换为析取(数据记录)逻辑程序,并应用析取技术(例如最小模型推理)来解决原始的更新问题。该方法扩展并集成了用于高效查询应答和完整性检查的标准技术。命中集的生成是通过针对最小目标的超稳态微积分和魔术集来进行的。

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