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- Title
自适应特征融合的迭代实体对齐方法.
- Authors
李婷婷; 邵 斐; 温天晓; 董 飒
- Abstract
Aiming at the problems of insufficient training data and low accuracy of long-tail entity alignment in the task of knowledge graph entity alignment, we proposed an iterative entity alignment method based on an adaptive feature fusion strategy and designed an iterative strategy to automatically expand the scale of the training data. This method utilized the structural information of the knowledge graph and utilized relationships, attributes, and entity name information as semantic information to assist alignment and improve alignment effectiveness. The experimental results on the dataset show that the proposed model performs well in the task of knowledge graph entity alignment.
- Publication
Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban), 2024, Vol 62, Issue 3, p629
- ISSN
1671-5489
- Publication type
Article
- DOI
10.13413/j.cnki.jdxblxb.2023296