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机构地区:[1]中国科学技术信息研究所,北京100038 [2]富媒体数字出版内容组织与知识服务重点实验室,北京100038
出 处:《情报理论与实践》2022年第8期130-137,共8页Information Studies:Theory & Application
基 金:国家重点研发计划项目“颠覆性技术识别理论、方法与专家预判系统”的研究成果之一,项目编号:2019YFA0707201。
摘 要:[目的/意义]科技创新日益重要,对特定领域技术进行监测与评估有助于把握科技发展脉络,发现热点技术,预测技术演化趋势,寻找科技创新突破口。[方法/过程]文章提出了一种基于科技文献增长率与关注度监测的技术评估方法。该方法利用技术列表匹配搜索科技文献中的技术并构建时序技术关联网络,在计算技术关注度和增长率基础上判别技术状态,进行综合分析并评估技术。[结果/结论]以人工智能领域为例开展实证研究发现:在技术关联网络中,节点度数越高越有可能为研究热点技术;具有高关注度、高增长率的技术之间具有更多关联关系。此外,基于技术关联网络对中介中心度和特征向量中心度进行对比实验,证明了所提方法的合理性。[Purpose/significance]Science and technology innovation has become more and more important.Monitoring and assessing technologies in specific fields could help researchers grasp the context of scientific and technological development,find hot technologies,predict the trend of technological evolution,and find breakthroughs.[Method/process]This paper proposes a technology assessment method via monitoring growth rate and attention measure of scientific literature.This method uses technology lists to match and search the technology in the scientific literature,and constructs technology association network with temporal information.On the basis of calculating technology attention and growth rate,it discriminates the technology state,makes a comprehensive analysis and evaluates the technology.[Result/conclusion]This paper takes artificial intelligence research field as an example for empirical research.Results show that the higher the degree of nodes in technology association network,the more likely it is to be the technology research hotspot.Technologies with high technical concern degree and high growth rate may have more links with other technologies.In addition,we make a comparative experiment on the centrality of intermediary and eigenvector to validity the proposed method.
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