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Knowledge Graphs: An Information Retrieval Perspective

机译：知识图表：信息检索透视

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摘要

In this survey, we provide an overview of the literature on knowledge graphs (KGs) in the context of information retrieval (IR). Modern IR systems can benefit from information available in KGs in multiple ways, independent of whether the KGs are publicly available or proprietary ones. We provide an overview of the components required when building IR, systems that leverage KGs and use a task-oriented organization of the material that we discuss. As an understanding of the intersection of IR and KGs is beneficial to many researchers and practitioners, we consider prior work from two complementary angles: leveraging KGs for information retrieval and enriching KGs using TR techniques. We start by discussing how KGs can be employed to support IR tasks, including document and entity retrieval. We then proceed by describing how IR, and language technology in general can be utilized for the construction and completion of KGs. This includes tasks such as entity recognition, typing, and relation extraction. We discuss common issues that appear across the tasks that we consider and identify future directions for addressing them. We also provide pointers to datasets and other resources that should be useful for both newcomers and experienced researchers in the area.
机译：在本调查中，我们在信息检索（IR）的背景下，我们在知识图表（KGS）上概述了文献。现代IR系统可以通过多种方式从公斤的信息中受益，独立于公斤是公开可用的或专有的。我们概述了构建IR，利用KGS的系统所需的组件，并使用我们讨论的任务化组织。作为对IR和KG的交汇处的理解有利于许多研究人员和从业者，我们考虑从两个互补角度开始工作：利用KGS获取信息检索和使用TR技术丰富KGS。我们首先讨论KGS如何用于支持IR任务，包括文档和实体检索。然后，我们通过描述IR和语言技术的施工和完成KGS的方式来进行。这包括实体识别，键入和关系提取等任务。我们讨论了我们考虑并确定未来对其的指示的常见问题。我们还向数据集和其他资源提供指针，这些资源应该对该地区的新人和经验丰富的研究人员有用。

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