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%。
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.
关键词
实体消歧 /
实体链接 /
加权重叠度 /
近邻传播聚类
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Key words
entity disambiguation /
entity linking /
weighted overlap relatedness /
affinity propagation clustering
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参考文献
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脚注
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基金
国家自然科学基金(61363044, 61175068, 61365010, 61462054, 61462055)
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