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基于特征加权重叠度的中文实体协同消歧方法
引用本文:线岩团,余正涛,洪旭东,张 磊,郭剑毅.基于特征加权重叠度的中文实体协同消歧方法[J].中文信息学报,2017,31(2):36-41.
作者姓名:线岩团  余正涛  洪旭东  张 磊  郭剑毅
作者单位:昆明理工大学 信息工程与自动化学院,云南 昆明 650500
基金项目:国家自然科学基金(61363044, 61175068, 61365010, 61462054, 61462055)
摘    要:该文针对中文实体消歧中的特征项部分匹配和协同消歧问题,提出基于特征加权重叠度的中文实体协同消歧方法。该方法利用实体指称上下文中多种特征的加权重叠度计算实体指称相似度,针对实体链接与消歧聚类约束,分类定义实体指称相似度计算方法,构建待消歧实体相似度矩阵,采用近邻传播聚类算法实现中文实体协同链接与消歧。基于CLP-2012评测数据的实验表明,提出的方法取得了较好的消歧效果,准确率、召回率和F值分别达到了84.01%、87.75%和85.65%。

关 键 词:实体消歧  实体链接  加权重叠度  近邻传播聚类  

Collaborative Entity Disambiguation Method Based on Weighted Feature Overlap Relatedness for Chinese
XIAN Yantuan,YU Zhengtao,HONG Xudong,ZHANG Lei,GUO Jianyi.Collaborative Entity Disambiguation Method Based on Weighted Feature Overlap Relatedness for Chinese[J].Journal of Chinese Information Processing,2017,31(2):36-41.
Authors:XIAN Yantuan  YU Zhengtao  HONG Xudong  ZHANG Lei  GUO Jianyi
Affiliation:Faculty of Information Engineering and Automation,Kunming University of Science and
Technology, Kunming, Yunnan 650500, China
Abstract:A collaborative entity disambiguation method based on weighted feature overlap relatedness is proposed in this paper. This method make use of weighted feature overlap relatedness for computing the similarity between entity names. We define some deferent similarity formulas for computing entity similarity matrix, then the affinity propagation clustering algorithm is used to get the disambiguation results. Evaluation on the CLP-2012 corpus shows that our method can achieve competitive performance, attains 84.01% precision, 87.75% recall and 85.65% F-score.
Keywords:entity disambiguation  entity linking  weighted overlap relatedness  affinity propagation clustering  
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