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Vadalog: A modern architecture for automated reasoning with large knowledge graphs
Information Systems ( IF 3.0 ) Pub Date : 2020-05-11 , DOI: 10.1016/j.is.2020.101528
Luigi Bellomarini , Davide Benedetto , Georg Gottlob , Emanuel Sallinger

The introduction of novel Datalog +/- fragments with good theoretical properties, together with the growing use of enterprise knowledge graphs motivated the development of Vadalog, a knowledge graph management system developed at the University of Oxford. It adopts Warded Datalog +/- as the core of its language for knowledge representation and reasoning, which exhibits a very good tradeoff between computational complexity of reasoning and expressive power, capturing PTIME data complexity while allowing ontological reasoning and full recursion. In this paper, we provide a detailed illustration of the Vadalog system, presenting: the essentials of the first implementation of Warded Datalog +/-; a comprehensive overview of the architecture with specific focus on runtime execution model, memory management, graph traversal strategies and join algorithms; and a detailed experimental evaluation.

This paper is a substantially expanded version of the AMW 2019 paper “Datalog-based reasoning for Knowledge Graphs”. To stand apart from previous works on the topic, our focus in this work shall be a comprehensive presentation of the architecture of the Vadalog system and showing how our techniques work together to provide a full-fledged KGMS. In particular, roughly half of this paper is new material created particularly for this comprehensive architectural view. This includes a new series of experiments designed to shed light on architectural choices and alternatives.



中文翻译:

Vadalog:具有大量知识图的自动推理的现代体系结构

具有良好理论特性的新型Datalog +/-片段的引入,以及企业知识图的日益广泛使用,促使了Vadalog的发展,Vadalog是牛津大学开发的知识图管理系统。它采用Warded Datalog +/-作为其语言的核心,用于知识表示和推理,在推理的计算复杂度和表达能力之间展现出很好的折衷,既可以捕获PTIME数据复杂性,又可以进行本体论推理和完全递归。在本文中,我们提供了Vadalog系统的详细说明,并提出了:Warded Datalog +/-的第一个实现的要点;全面的体系结构概述,特别关注运行时执行模型,内存管理,图形遍历策略和联接算法;

本文是AMW 2019年论文``知识图的基于数据记录的推理''的实质性扩展版本。为了与以前在该主题上的作品脱颖而出,我们在这项工作中的重点应该是对Vadalog系统的体系结构的全面介绍,并展示我们的技术如何协同工作以提供完整的KGMS。特别是,本文的大约一半是专为这种全面的架构视图而创建的新材料。这包括一系列旨在阐明架构选择和替代方案的新实验。

更新日期:2020-05-11
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