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A Graph-based Similarity Measure between Wikipedia Concepts and Its Application in Entity Linking System
Zhang Tao; Liu Kang; Zhao Jun
2015
发表期刊Journal of Chinese Information Processing
期号29页码:58-67
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.
关键词Similarity Measure
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20635
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.
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