RDF知识图分析方法综述

Maria-Evangelia Papadaki, Yannis Tzitzikas, M. Mountantonakis
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引用次数: 2

摘要

有几种用RDF(资源描述框架)表示的知识图,它们聚合/集成来自不同来源的数据,以提供统一的访问服务并支持深刻的分析。我们在生活的几乎每个领域都观察到这种趋势。然而,提供有效、高效和用户友好的分析服务和系统是相当具有挑战性的。在本文中,我们概述了能够对RDF表示的KGs进行分析查询的方法、系统和工具。我们确定了主要的挑战,区分了分析查询的两个主要类别(特定于领域的和与质量相关的),以及基于RDF的五种分析方法。然后,我们简要地描述了每个类别的工作以及相关的方面,如效率和可视化。我们希望这个集合对研究人员和工程师有用,以提高知识图分析方法的功能和用户友好性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Brief Survey of Methods for Analytics over RDF Knowledge Graphs
There are several Knowledge Graphs expressed in RDF (Resource Description Framework) that aggregate/integrate data from various sources for providing unified access services and enabling insightful analytics. We observe this trend in almost every domain of our life. However, the provision of effective, efficient, and user-friendly analytic services and systems is quite challenging. In this paper we survey the approaches, systems and tools that enable the formulation of analytic queries over KGs expressed in RDF. We identify the main challenges, we distinguish two main categories of analytic queries (domain specific and quality-related), and five kinds of approaches for analytics over RDF. Then, we describe in brief the works of each category and related aspects, like efficiency and visualization. We hope this collection to be useful for researchers and engineers for advancing the capabilities and user-friendliness of methods for analytics over knowledge graphs.
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