文献类型：期刊文献

英文题名：Integration of multiple terminology bases: a multi-view alignment method using the hierarchical structure

作者：Hu, Peihong[1];Ye, Qi[1];Zhang, Weiyan[1];Liu, Jingping[1];Ruan, Tong[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

年份：2023

卷号：39

期号：11

外文期刊名：BIOINFORMATICS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001189254800004)】；

基金：This work was supported by the National Natural Science Foundation of China [62306112]; Shanghai Sailing Program [23YF1409400]; and the National Key Research and Development Program of China [2021YFC2701800, 2021Y FC2701801].

语种：英文

摘要：Motivation: In the medical field, multiple terminology bases coexist across different institutions and contexts, often resulting in the presence of redundant terms. The identification of overlapping terms among these bases holds significant potential for harmonizing multiple standards and establishing unified framework, which enhances user access to comprehensive and well-structured medical information. However, the majority of terminology bases exhibit differences not only in semantic aspects but also in the hierarchy of their classification systems. The conventional approaches that rely on neighborhood-based methods such as GCN may introduce errors due to the presence of different superordinate and subordinate terms. Therefore, it is imperative to explore novel methods to tackle this structural challenge. Results: To address this heterogeneity issue, this paper proposes a multi-view alignment approach that incorporates the hierarchical structure of terminologies. We utilize BERT-based model to capture the recursive relationships among different levels of hierarchy and consider the interaction information of name, neighbors, and hierarchy between different terminologies. We test our method on mapping files of three medical open terminologies, and the experimental results demonstrate that our method outperforms baseline methods in terms of Hits@1 and Hits@10 metrics by 2%.