Advances in Knowledge Fusion Research in Medical Domain

doi:10.3778/j.issn.1002-8331.2309-0406

Abstract

Abstract: Knowledge fusion in the medical domain aims to integrate medical knowledge scattered in various knowledge graphs or different data sources to form a more comprehensive knowledge graph, which plays a promoting role in improving knowledge quality, expanding scale, augmenting the utilization and sharing of medical knowledge, and so on. Around the issues and solutions of knowledge fusion, firstly, the definition, evaluation indexes and datasets in medical knowledge fusion are systematically sorted out. The problems and challenges in the process of knowledge fusion are discussed. Then, from the two dimensions of problems and technologies, the advantages and disadvantages of various methods for entity alignment and entity linking tasks in current knowledge fusion are summarized. The solutions for each type in medical knowledge fusion are discussed and summarized in detail. Finally, the paper summarizes and looks at the development direction of knowledge fusion in medical domain.

Key words: medical domain, knowledge fusion, entity alignment, entity linking

摘要： 医学领域知识融合旨在将分散在各个知识图谱或不同数据源中的医学知识进行整合，形成一个更全面的知识图谱，在提高知识质量、扩大规模、提高医学知识利用率和共享性等方面具有促进作用。围绕知识融合的问题和解决方案，首先系统地梳理了医学领域知识融合的定义、评价指标及数据集；分类讨论了知识融合过程中存在的问题与挑战；然后从问题、技术两个维度，综述了目前知识融合中实体对齐、实体链接任务各方法的优势与不足；详细讨论和总结了医学领域知识融合每一类问题的相关解决方案；最后，总结并展望了医学领域知识融合的发展方向。

关键词: 医学领域, 知识融合, 实体对齐, 实体链接

PENG Lin, SONG Jun, XIONG Lingzhu, DU jianqiang, YE Qing, LIU Andong. Advances in Knowledge Fusion Research in Medical Domain[J]. Computer Engineering and Applications, 2024, 60(9): 48-64.

彭琳, 宋珺, 熊玲珠, 杜建强, 叶青, 刘安栋. 医学领域知识融合研究进展[J]. 计算机工程与应用, 2024, 60(9): 48-64.

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