构建、维护和使用知识库:来自战壕的报告

Omkar Deshpande, Digvijay S. Lamba, Michel Tourn, Sanjib Das, S. Subramaniam, A. Rajaraman, Venky Harinarayan, A. Doan
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引用次数: 95

摘要

知识库(KB)包含一组概念、实例和关系。在过去的十年中,已经建立了大量的KBs,并用于支持越来越多的应用程序。然而,尽管有这些活动,令人惊讶的是,关于在工业中构建、维护和使用此类KBs的端到端过程的文章却很少。本文描述了这一过程。特别是,我们描述了我们如何在海湾地区的初创公司Kosmix以及后来在沃尔玛的开发和研究实验室WalmartLabs建立、更新和管理大型知识库。我们将讨论如何使用这个知识库来支持一系列应用,包括查询理解、深度网络搜索、上下文广告、社交媒体事件监控、产品搜索、社交礼品和社交挖掘。最后,我们将讨论如何组织KB团队,以及从中吸取的经验教训。本文的目标是提供一个真实的案例研究,并为数据管理应用程序的构建、维护和使用知识库的新兴方向做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building, maintaining, and using knowledge bases: a report from the trenches
A knowledge base (KB) contains a set of concepts, instances, and relationships. Over the past decade, numerous KBs have been built, and used to power a growing array of applications. Despite this flurry of activities, however, surprisingly little has been published about the end-to-end process of building, maintaining, and using such KBs in industry. In this paper we describe such a process. In particular, we describe how we build, update, and curate a large KB at Kosmix, a Bay Area startup, and later at WalmartLabs, a development and research lab of Walmart. We discuss how we use this KB to power a range of applications, including query understanding, Deep Web search, in-context advertising, event monitoring in social media, product search, social gifting, and social mining. Finally, we discuss how the KB team is organized, and the lessons learned. Our goal with this paper is to provide a real-world case study, and to contribute to the emerging direction of building, maintaining, and using knowledge bases for data management applications.
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