查询可能性RDF数据的通用框架

Amna Abidi, Mohamed Anis Bach Tobji, A. Hadjali, B. B. Yaghlane
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引用次数: 3

摘要

网络上的数据常常充满了不确定性。这是由于网络的开放性和来源的多样性,使得收集数据的可靠性受到质疑。在本文中,我们解决了资源描述框架(RDF)数据的不确定性问题。这里的不确定性用富可能性理论来表示。为此,我们描述了一个通用框架,用于在可能性RDF数据上支持类似sparql的查询,我们将其称为Pi-SPARQL。为了描述可能的需求,Pi-SPARQL以以下两种方式扩展SPARQL。首先,通过将图模式的解决方案与可能性度量相关联,它允许以一种简单的方式向基于RDF的应用程序表示可能性程度。然后,Pi-SPARQL提出解决方案映射和评估的适当语义,也就是说,它使用户能够处理不确定的RDF数据规范,并访问与解决方案相关的可能性度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A General Framework for Querying Possibilistic RDF Data
Data on the Web is often pervaded with uncertainty. This is due to the openness of the Web and variety of sources which makes reliability of collected data questionable. In this paper, we address the Resource Description Framework (RDF) data uncertainty problem. Uncertainty here is represented by the rich possibility theory. To this end, we describe a general framework for supporting SPARQL-like queries on possibilistic RDF data, that we denote Pi-SPARQL. To describe possibilistic requirements, Pi-SPARQL extends SPARQL in the following two ways. First, it allows expressing possibility degrees to RDF based applications in an easy manner by associating the solutions for graph patterns with possibility measures. Then, Pi-SPARQL proposes appropriate semantics of the solution mappings and evaluation, i.e., it enables users to deal with uncertain RDF data specifications and access the possibility measures associated to the solutions.
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