%A Li Wenna, Zhang Zhixiong %T Entity Alignment Method for Different Knowledge Repositories with Joint Semantic Representation %0 Journal Article %D 2021 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2021.0143 %P 1-9 %V 5 %N 7 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_5115.shtml} %8 2021-07-25 %X

[Objective] This paper combines the structure and semantic information of knowledge, aiming to create a better entity alignment method for different knowledge repositories. [Methods] First, we used the TransE model to represent the structure of entities, and used the BERT model to represent their semantic information. Then, we designed an entity alignment method based on the BTJE model (BERT and TransE Joint model for Entity alignment). Finally, we use the siamese network model to finish entity alignment tasks. [Results] We examined the new method with DBP-WD and DBP-YG datasets. Their optimal MRR values reached 0.521 and 0.413, while the Hits@1 reached 0.542 and 0.478. These results were better than those of the traditional models. [Limitations] The size of our experimental data set needs to be expanded, which will further evaluate the performance of the proposed method. [Conclusions] Our new method could effectively finish entity alignment tasks for different knowledge bases.