计算机应用研究2017，Vol.34Issue(10)：2909-2914,6.DOI:10.3969/j.issn.1001-3695.2017.10.007
面向实体链接的多特征图模型实体消歧方法
Entity disambiguation method based on multi-feature fusion graph model for entity linking
摘要
Abstract
Entity linking is the task of linking name mention in a document with their referent entities in a knowledge base.The accuracy of the named entity disambiguation affects the accuracy of the entity linking directly.According to the named entity disambiguation in the technology of Chinese entity linking,this paper proposed a disambiguation method based on multifeature fusion.Firstly,it used the Chinese Wikipedia as the knowledge base.It made full use of Wikipedia's rich structural information,such as the abstract,the category,the ambiguity page,the anchor text,and so on.After that,it extracted varieties of the semantic features to measure the semantic similarities between the context of entity mention and the information of the candidate entities in Wikipedia.And then,it modeled a graph which represented the relationship between the name mention and the candidate entities with these similarities.At last,it used the PageRank algorithm to rank the candidate entities and chose the top1 entity as a result of the entity linking.Compared with the baseline system which focused on expression characteristics of the name mentions,the value of F increased by 9％.The proposed approach can improve the entity linking system's performance.关键词
中文实体链接/实体消歧/语义特征/图模型Key words
Chinese entity linking/entity disambiguation/semantic features/graph model分类
信息技术与安全科学引用本文复制引用
高艳红,李爱萍,段利国..面向实体链接的多特征图模型实体消歧方法[J].计算机应用研究,2017,34(10):2909-2914,6.基金项目
国家自然科学基金资助项目(61572345) （61572345）
