计算机科学
工作流程
领域知识
知识图
光学(聚焦)
知识管理
背景(考古学)
领域(数学分析)
软件工程
人工智能
数据库
数学
物理
数学分析
古生物学
光学
生物
作者
Luigi Bellomarini,Daniele Fakhoury,Georg Gottlob,Emanuel Sallinger
标识
DOI:10.1109/icde.2019.00011
摘要
Adopting a mature AI strategy is fundamental for modern knowledge companies to govern the proliferation of smart AI-driven applications and to coordinate them within coherent knowledge workflows. We propose knowledge graphs as the reference technology for the enterprise AI context, i.e., the complex of entities, properties and relationships that shape a business domain and constitute a common backbone for all AI-driven applications. We contribute and discuss principles to design software architectures for AI-driven applications based on knowledge graphs. We focus on the Vadalog system, a successful knowledge graph middleware from the University of Oxford and show knowledge graphs in action in a number of use cases from the financial domain.
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