A Cross-Domain Ontology Semantic Representation Based on NCBI-BlueBERT Embedding  

作　　者：ZHAO Lingling WANG Junjie WANG Chunyu GUO Maozu 

机构地区：[1]Faculty of Computing,Harbin Institute of Technology,Harbin 150001,China [2]Department of Medical Informatics,School of Biomedical Engineering and Informatics,Nanjing Medical University,Nanjing 211166,China [3]Beijing Key Laboratory of Intelligent Processing for Building Big Data,Beijing 100044,China [4]School of Electrical and Information Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China

出　　处：《Chinese Journal of Electronics》2022年第5期860-869,共10页电子学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(62171164,62102191,61872114,62131004).

摘　　要：A common but critical task in biological ontologies data analysis is to compare the difference between ontologies.There have been numerous ontologybased semantic-similarity measures proposed in specific ontology domain,but it still remains a challenge for crossdomain ontologies comparison.An ontology contains the scientific natural language description for the corresponding biological aspect.Therefore,we develop a new method based on natural language processing(NLP)representation model bidirectional encoder representations from transformers(BERT)for cross-domain semantic representation of biological ontologies.This article uses the BERT model to represent the word-level of the ontologies as a set of vectors,facilitating the semantic analysis or comparing the biomedical entities named in an ontology or associated with ontology terms.We evaluated the ability of our method in two experiments:calculating similarities of pair-wise disease ontology and human phenotype ontology terms and predicting the pair-wise of proteins interaction.The experimental results demonstrated the comparative performance.This gives promise to the development of NLP methods in biological data analysis.

关 键 词：ONTOLOGY Semantic representation Semantic similarity Protein-protein interaction 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]