Knowledge Graph Analysis of Domestic Named Entity Recognition Based on CiteSpace
Named Entity Recognition(NER)is an important task in the field of Natural Language Processing(NLP).Quantitative review of the literature process of NER technology is conducive to the breakthrough development of NER and even NLP technology in the future.At present,a large number of scholars have reviewed the NER tasks.However,these review methods based on traditional bibliometrics not only rely too much on expert experience,but also can not directly present the change of knowledge paradigm.Therefore,this paper,driven by the Chinese core literature of CNKI and based on CiteSpace,presents the Knowledge Graph display and data mining analysis of domestic NER technology.The analysis results show that the domestic research on NER has formed two rapid development periods based on data drive from 2016.The form of"local university+provincial laboratory"has become the mainstream of domestic institutional cooperation."Deep Learning""Knowledge Graph""entity recognition""information extraction""Neural Network"and"word vector"are the hot spots of domestic NER research.Future research on NER tends to apply landing,data enhancement and knowledge extraction.
Named Entity RecognitionCiteSpaceKnowledge GraphCNKI
国家科技期刊平台
NSTL
万方数据
