典型文献
Biomedical entity linking based on less labeled data
文献摘要：
1 Introduction
Biomedical entity linking aims to align the natural language entity to the knowledge base concept referring to the same real-world object.Recent solutions in the biomedical field focus on the embedding-based method to jointly model the texts and the knowledge graph into a multi-dimensional entity space.However,the task of a biomedical entity linking is still facing tough challenges:1)The ambiguity of natural language descriptions,including polysemy and abbreviation,is an urgent problem to be solved.2)Biomedical texts lack detailed annotations.The weakly labeled data brings a huge challenge to entity linking.Although some heuristic methods have been used for semi-structured data analysis in the field of bioin-formatics,it is still very difficult to automatically integrate biomedical literature and structured knowledge graph with a reliable algorithm.
文献关键词：
中图分类号：
作者姓名：
Yu HU;Derong SHEN;Tiezheng NIE;Yue KOU;Ge YU
作者机构：
School of Computer Science and Engineering,Northeastern University,Shenyang 110819,China
文献出处：
引用格式：
[1]Yu HU;Derong SHEN;Tiezheng NIE;Yue KOU;Ge YU-.Biomedical entity linking based on less labeled data)[J].计算机科学前沿,2022(03):209-211
A类：
Biomedical,polysemy,formatics
B类：
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AB值：
0.559402
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