基于异类数据和语义建构的新兴技术弱信号识别研究

Weak Signal Detection and Identification with Heterogeneous Data and Semantic Construction

当前商业竞争不断加剧,创新和产品的迭代周期不断加快,识别未来新兴技术的早期弱信号,具有重要的战略意义。本文提出了一种基于异类数据和语义建构的新兴技术弱信号识别新方法。首先,以文献数据作为新兴技术弱信号识别的分析对象,探索使用文档离群性和文本相异性指标筛选异类数据,并构建合适的量化评估方法;其次,通过改进TF-IDF(term frequency-inverse document frequency)算法和组合图法,抽取弱信号关键词表征术语;最后,基于意义建构理论抽取术语上下文语境,挖掘并解析弱信号含义,以实现新兴技术弱信号识别。本文以量子信息领域作为实证研究对象,识别出当前量子信息领域新兴技术弱信号包括量子点吸附、量子保密协议、量子点医学和量子博弈等。研究结论证实了本文方法的有效性,可为决策者和技术研发人员提供决策支持。

Business competition is intensifying,and the iteration cycle of innovation and products is accelerating.Thus,identifying the weak early signals of emerging technologies is of significant strategic importance.This study explores a novel method for weak signal detection and identification using heterogeneous data and semantic construction.First,heterogeneous data are filtered through document outlines and text dissimilarities based on academic articles.Second,weak signals represented by keyword terms are extracted by improved term frequency-inverse document frequency(TF-IDF)and the combination graph method.Finally,the context of the terms is obtained through semantic construction and mining to explain the meaning of weak signals,thereby identifying the weak signals of emerging technologies.Taking the field of quantum information as an example,this study identifies the weak signals of current emerging technologies,including quantum theory of dot adsorption,private agreement,dot medicine,and quantum games.The results confirm the effectiveness of the method for weak signal detection and identification.The method is expected to be helpful for science and technology managers in research decision-making.