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作 者:侯艳辉[1] 陈荣 王家坤[1] Hou Yanhui;Chen Rong;Wang Jiakun(College of Economics and Management,Shandong University of Science and Technology,Qingdao 266590)
出 处:《情报学报》2025年第2期157-170,共14页Journal of the China Society for Scientific and Technical Information
基 金:山东省社会科学规划研究项目“全媒体时代舆情信息研判与治理体系研究”(22DGLJ27)。
摘 要:针对目前颠覆性技术识别过程中忽略技术演化特征的问题,本文提出一种考虑技术生命周期阶段性和特征异质性的颠覆性技术早期识别方法。首先,采用Sentence-BERT (sentence bidirectional encoder representation from transformers)对专利摘要进行向量化。其次,构建过滤识别系统。第一层使用LOCI (local outlier factor with constraint integration)异常检测算法识别离群专利并分类;第二层,采用S曲线生命周期识别,对处于成熟期的专利类别进行过滤;第三层,对萌芽阶段的专利进行创新性测度;第四层,对成长阶段的专利文本、技术报道数据进行颠覆性测度,完成过滤。最后,以量子信息技术领域为例,阐述该识别方法的应用过程。研究结果表明,量子信息领域共发现三个萌芽期颠覆性主题和三个成长期颠覆性主题,与官方发布的报告进行对比,结果一致,验证了本文方法的可行性与有效性。s.Second,a filtering identification system is constructed:the first layer employs the local outlier factor with constraint integration(LOCI)anomaly detection algorithm to identify and classify outlier patents;the second layer uses an S-curve life cycle identification to filter patents in the maturity stage;the third layer measures the innovativeness of patents in the budding stage;and the fourth layer evaluates the disruptive nature of the patent text and technology reporting data in the growth stage to finalize the filtering process.Finally,the field of quantum information technology is used as a case study to illustrate this method.The study identifies three disruptive themes in the germination and growth stages,which align with the authoritative reports,verifying the feasibility and effectiveness of the proposed method.
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