典型文献
Distant supervised relation extraction based on residual attention
文献摘要：
1 Introduction
Relation extraction refers to extracting the semantic relation between entities from unstructured text data to form triple data(entity e1,entity e2,relation r)that is easy to for computer processing.Distant Supervised Relation Extraction(DSRE)[1]obtains relation triples by the heuristic alignment between the knowledge base and large-scale text.For example,if the relation between"Steve Jobs"and"Apple"in the knowledge base is"Founder",the sentences containing these two entities in the text will be used as examples of the relation"Founder"to train the relation extraction model.This method can generate a large amount of training data,but it is easy to introduce noise labeling,so reducing the influence of noise labeling has become a research focus.
文献关键词：
中图分类号：
作者姓名：
Zhiyun ZHENG;Yun LIU;Dun LI;Xingjin ZHANG
作者机构：
School of Information Engineering,Zhengzhou University,Zhengzhou 450001,China
文献出处：
引用格式：
[1]Zhiyun ZHENG;Yun LIU;Dun LI;Xingjin ZHANG-.Distant supervised relation extraction based on residual attention)[J].计算机科学前沿,2022(06):160-162
A类：
Relation,DSRE
B类：
Distant,supervised,relation,extraction,residual,attention,Introduction,refers,extracting,semantic,between,entities,from,unstructured,text,data,form,entity,e1,e2,that,easy,computer,processing,Supervised,Extraction,obtains,triples,by,heuristic,alignment,knowledge,large,scale,For,if,Steve,Jobs,Apple,Founder,sentences,containing,these,two,will,used,examples,model,This,method,can,generate,amount,training,but,introduce,noise,labeling,so,reducing,influence,has,become,research,focus
AB值：
0.5746
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