结合多重嵌入表示的中文知识图谱补全

陈跃鹤,谈川源,陈文亮,贾永辉,何正球

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中文信息学报 ›› 2023, Vol. 37 ›› Issue (1) : 54-63.
知识表示与知识获取

结合多重嵌入表示的中文知识图谱补全

  • 陈跃鹤,谈川源,陈文亮,贾永辉,何正球
作者信息 +

Chinese Knowledge Graph Complementation with Multiple Embeddings

  • CHEN Yuehe,TAN Chuanyuan,CHEN Wenliang,JIA Yonghui,HE Zhengqiu
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摘要

近年来,随着知识图谱相关技术的不断发展,各方面研究对知识图谱本身的需求也不断加强。然而现有的知识图谱无法完全覆盖整个真实世界,同时在知识正确性以及时效性等方面存在问题,这使得知识图谱补全越来越受到研究者的关注。在中文环境下,知识图谱补全任务又呈现出与英文图谱补全任务不同的特性。该文对中/英知识图谱补全任务进行了对比分析,将中文图谱中出现的错误进行了归类。根据该分析结果,该文提出将三元组中实体和关系嵌入表示、实体和关系描述文本嵌入表示结合的链接预测方法MER-Tuck,该方法利用外部的语义补充来加强矩阵分解模型的学习能力。为了验证该方法的有效性,该文为中文知识图谱补全任务构建了新数据集。在该数据集上将该文的方法与主流的链接预测方法进行比较,实验结果表明该文所提方法是有效的。

Abstract

In recent years, knowledge graph complementation attracts more and more attentions from researchers. This paper presents a comparative analysis of the Chinese/English knowledge graph complementation tasks with a focus on the errors in Chinese knowledge graphs. It further proposes MER-Tuck, a link prediction method combining the embeddings for the entity and relation, and the embeddings for text describing entity and relation. This method enhances the learning ability of the matrix decomposition via external semantic information. A dataset is constructed in this paper for the Chinese knowledge graph complementation task. And Experiments on this dataset show that the proposed method is effective.

关键词

知识图谱 / 知识图谱补全 / 链接预测

Key words

knowledge graph / knowledge graph complement / link prediction

引用本文

导出引用
陈跃鹤,谈川源,陈文亮,贾永辉,何正球. 结合多重嵌入表示的中文知识图谱补全. 中文信息学报. 2023, 37(1): 54-63
CHEN Yuehe,TAN Chuanyuan,CHEN Wenliang,JIA Yonghui,HE Zhengqiu. Chinese Knowledge Graph Complementation with Multiple Embeddings. Journal of Chinese Information Processing. 2023, 37(1): 54-63

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基金

国家自然科学基金(61936010);江苏省高校优势学科建设工程资助项目
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