迈向LarKC:一个网络级推理平台

D. Fensel, F. V. Harmelen, Bosse Andersson, P. Brennan, H. Cunningham, Emanuele Della Valle, F. Fischer, Zhisheng Huang, A. Kiryakov, T. Lee, L. Schooler, Volker Tresp, S. Wesner, M. Witbrock, N. Zhong
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引用次数: 155

摘要

当前的语义Web推理系统不能扩展到它们最热门的应用程序的需求,例如分析来自数百万移动设备的数据、处理tb级的科学数据,以及在拥有数千名知识工作者的企业中进行内容管理。在本文中,我们提出了构建大型知识碰撞器的计划,这是一个用于大规模分布式不完全推理的平台,将消除这些可扩展性障碍。这是通过(i)丰富当前基于逻辑的语义Web推理方法来实现的,(ii)采用认知启发的方法和技术,以及(iii)构建分布式推理平台,并在高性能计算集群上和通过“在家计算”实现。在本文中,我们将讨论LarKC技术如何超越Web规模推理的最新技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards LarKC: A Platform for Web-Scale Reasoning
Current semantic Web reasoning systems do not scale to the requirements of their hottest applications, such as analyzing data from millions of mobile devices, dealing with terabytes of scientific data, and content management in enterprises with thousands of knowledge workers. In this paper, we present our plan of building the large knowledge collider, a platform for massive distributed incomplete reasoning that will remove these scalability barriers. This is achieved by (i) enriching the current logic-based semantic Web reasoning methods, (ii) employing cognitively inspired approaches and techniques, and (iii) building a distributed reasoning platform and realizing it both on a high-performance computing cluster and via "computing at home". In this paper, we will discuss how the technologies of LarKC would move beyond the state-of-the-art of Web scale reasoning.
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