期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Microsoft Concept Graph:Mining Semantic Concepts for Short Text Understanding 被引量:6
1
作者 Lei Ji Yujing Wang +3 位作者 Botian Shi Dawei Zhang Zhongyuan Wang Jun Yan 《Data Intelligence》 2019年第3期238-270,共33页
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.Mic... 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 Ads relevance.Since the release in 2016,Microsoft Concept Graph has received more than 100,000 pageviews,2 million API calls and 3,000 registered downloads from 50,000 visitors over 64 countries. 展开更多
关键词 Knowledge extraction CONCEPTUALIZATION Text understanding
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部