Article(id=1242138666794037753, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242138640944542126, articleNumber=null, orderNo=17, doi=10.3981/j.issn.1000-7857.2020.20.015, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1588003200000, receivedDateStr=2020-04-28, revisedDate=1590508800000, revisedDateStr=2020-05-27, acceptedDate=null, acceptedDateStr=null, onlineDate=1604480702397, onlineDateStr=2020-11-04, pubDate=1603814400000, pubDateStr=2020-10-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1604480702397, onlineIssueDateStr=2020-11-04, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774078535980, creator=sys-migrate, updateTime=1774078535980, updator=sys-migrate, issue=Issue{id=1242138640944542126, tenantId=1146029695717560320, journalId=1146031591421210625, year='2020', volume='38', issue='20', pageStart='1', pageEnd='136', issueExtLink='null', onlineDate='null', pubDate='1603814400000', pubDateStr='2020-10-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774078529817, creator='sys-migrate', updateTime=1774078529817, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=97, endPage=105, ext={EN=ArticleExt(id=1242138672527646856, articleId=1242138666794037753, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=The disruptive technology of recognition based on topic mutation detection: With the drone technology as an example, columnId=1150494644690366681, journalTitle=Science & Technology Review, columnName=Papers, runingTitle=null, highlight=null, articleAbstract=The disruptive technology is of great strategic significance for the leap-forward development of China's technological innovation. In order to get rid of the situation of the lack of original innovation capabilities, and to deal with the varied key core technologies, the subversive technology identification is of great significance. This paper takes the UAV technology field as an example, reviews 2812 papers and patent data collected in the Web of Science (Wos) paper database and Derwent patent database from 2005 to 2019, with the technology based on the LDA-LSTM text classification algorithm Theme, and the CiteSpace to build a co-occurrence network, to realize the theme mutation detection from the perspective of mutation weight ranking and mutation time period and mutation co-word clustering knowledge map, and to identify the brain-computer interface technology and the gesture control in the UAV interaction The technology is a disruptive technology in this field. Finally, the validity of the recognition framework is verified through patents in the related papers in the field of the drone technology in 2020., authors=LIU Zhongbao, KANG Jiaqi, ZHANG Jing, authorsList=LIU Zhongbao, KANG Jiaqi, ZHANG Jing, authorCompany=School of Software, North University of China, Taiyuan 030051, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=fQqD8q5vWxlYHYbBjejP+w==, pdfFileSize=3318456, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242138670271111296, articleId=1242138666794037753, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=基于主题突变检测的颠覆性技术识别——以无人机技术领域为例, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=颠覆性技术对实现中国科技创新跨越式发展具有重要战略意义。以无人机技术领域为例，获取Web of Science论文数据库和德温特（Derwent）专利数据库2005—2019年收录的2812篇论文与专利数据，基于LDA-LSTM文本分类算法得到技术主题，采用CiteSpace构建共现网络，从突变权重排序及突变时间段和突变共词聚类知识图谱2个角度进行主题突变检测，进而识别出无人机交互技术中的脑机接口技术及手势控制技术为该领域内的颠覆性技术，通过2020年无人机技术领域相关论文专利验证了识别框架的有效性。, authors=刘忠宝, 康嘉琦, 张静, authorsList=刘忠宝, 康嘉琦, 张静, authorCompany=中北大学软件学院, 太原 030051, correspAuthors=null, authorNote=刘忠宝,教授,研究方向为数据挖掘、机器学习、信息资源推荐,电子信箱:liuzb@nuc.edu.cn;康嘉琦(共同第一作者),硕士研究生,研究方向为数据挖掘、智能信息处理, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=BTPDvfyM7vIbWQ0GGZ3Asw==, pdfFileSize=3318456, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, 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