分类: 计算机科学 >> 计算机科学的集成理论 提交时间: 2022-11-27 合作期刊: 《数据智能(英文)》
摘要: Knowlege is important for text-related applications. In this paper, we introduce Microsoft Concept Graph, a knowledge graph engine that provides concept tagging APIs to facilitate the understanding of human languages. Microsoft Concept Graph is built upon Probase, a universal probabilistic taxonomy consisting of instances and concepts mined from the Web. We start by introducing the construction of the knowledge graph through iterative semantic extraction and taxonomy construction procedures, which extract 2.7 million concepts from 1.68 billion Web pages. We then use conceptualization models to represent text in the concept space to empower text-related applications, such as topic search, query recommendation, Web table understanding and advertisements relevance. Since the release in 2016, Microsoft Concept Graph has received more than 100,000 page views, 2 million API calls and 3,000 registered downloads from 50,000 visitors over 64 countries.