实现声明式比较:应用于功能依赖性

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Lhouari Nourine , Jean-Marc Petit , Simon Vilmin
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引用次数: 0

摘要

在现实生活中,由于不确定性、错误测量、缺失值或不良输入等原因,数据质量往往很差。这个问题阻碍了每个数据库管理系统的一个隐含但至关重要的操作:等式测试。事实上,相等性归根结底是一种依赖于上下文的操作,有多种解释。在实践中,如何处理不同类型的相等关系只能由程序员来解决,他们不得不在代码中与这些解释做斗争。我们引入了一个基于网格的声明式框架来解决这个问题。它允许在高度抽象的层次上为等式指定多种语义。除了元组相等之外,我们还根据我们的框架研究了函数依赖(FDs)。首先,我们定义了抽象 FD,对经典 FD 进行了概括。这就需要考虑对等价的特殊解释:现实。在现实性和可能/确定答案的基础上,我们引入了可能/确定 FD,并给出了一些复杂性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards declarative comparabilities: Application to functional dependencies

In real life, data are often of poor quality as a result, for instance, of uncertainty, mismeasurements, missing values or bad inputs. This issue hampers an implicit yet crucial operation of every database management system: equality testing. Indeed, equality is, in the end, a context-dependent operation with a plethora of interpretations. In practice, the treatment of different types of equality is left to programmers, who have to struggle with those interpretations in their code. We introduce a lattice-based declarative framework to address this problem. It allows specification of numerous semantics for equality at a high level of abstraction. To go beyond tuple equality, we study functional dependencies (FDs) in the light of our framework. First, we define abstract FDs, generalizing classical FDs. These lead to the consideration of particular interpretations of equality: realities. Building upon realities and possible/certain answers, we introduce possible/certain FDs and give some complexity results.

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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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