计算机与数字工程2025，Vol.53Issue(2)：403-408,6.DOI:10.3969/j.issn.1672-9722.2025.02.018
一种基于特征嵌入的知识图谱实体对齐方法
A Method for Knowledge Graph Entity Alignment Based on Feature Embedding
摘要
Abstract
In recent years,knowledge graphs have been widely applied to many fields including intelligent question and an-swer,machine translation,and entity retrieval.The neighborhood structures of co-referred entities are usually non-isomorphic in different knowledge graphs,and to solve the problem of inadequate representation of heterogeneous knowledge graphs and the un-der-utilization of entity features.This paper proposes an entity alignment method based on the joint embedding of multiple features,using entity relationship features,entity attribute features and entity name features in knowledge graphs to train the embedding rep-resentation of entities.The entity-relationship path is used as the training data for the entity-relationship features to solve the prob-lem of narrow coverage of the relational triples.The experiments show that entity relationship features have a significant effect on the entity alignment task,and the richer the entity relationships in the graph the better the alignment results.The model shows a signifi-cant improvement in entity alignment results compared with the single-feature model.关键词
知识图谱/知识融合/实体对齐/预训练模型Key words
knowledge graph/knowledge fusion/entity alignment/pre-training model分类
信息技术与安全科学引用本文复制引用
栾瑞鹏,郝瑞东..一种基于特征嵌入的知识图谱实体对齐方法[J].计算机与数字工程,2025,53(2):403-408,6.基金项目
国家自然科学基金项目(编号:6170021755)资助. （编号:6170021755）
