A Graph-based Similarity Measure between Wikipedia Concepts and Its Application in Entity Linking System

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 自然语言处理

	A Graph-based Similarity Measure between Wikipedia Concepts and Its Application in Entity Linking System
	Zhang Tao; Liu Kang; Zhao Jun
刊名	Journal of Chinese Information Processing
	2015
期号	29 页码:58-67
关键词	Similarity Measure
英文摘要	Entity linking is the task of map entity mentions in a document to their entities in a knowledge base (KB). In this paper, we briefly introduce the traditional entity linking system and point out the key problem of entity linking system-the semantic similarity measure between the content of entity mention and the document of the candidate entity. And then, we propose a novel semantic relatedness measure between Wikipedia concepts based on the graph structure of Wikipedia. With this similarity measure, we present a novel learning to rank framework which leverage the rich semantic information derived from Wikipedia to deal with the entity lining task. Experiment results show that the performance of the system is comparable to the state-of-art result.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/40859]
专题	模式识别国家重点实验室_自然语言处理
通讯作者	Liu Kang
推荐引用方式 GB/T 7714	Zhang Tao,Liu Kang,Zhao Jun. A Graph-based Similarity Measure between Wikipedia Concepts and Its Application in Entity Linking System[J]. Journal of Chinese Information Processing,2015(29):58-67.
APA	Zhang Tao,Liu Kang,&Zhao Jun.(2015).A Graph-based Similarity Measure between Wikipedia Concepts and Its Application in Entity Linking System.Journal of Chinese Information Processing(29),58-67.
MLA	Zhang Tao,et al."A Graph-based Similarity Measure between Wikipedia Concepts and Its Application in Entity Linking System".Journal of Chinese Information Processing .29(2015):58-67.