[Purpose/significance] Based on a metrological perspective, this study intends to identify emerging research technologies that are "currently in the scientific research stage and have not yet fully entered the industrial R&D landing" through the quantitative evaluation of the characteristics of emerging technologies. [Method/process] Specifically, with the help of the Node2Vec network representation method, this paper learned the vector representation of technical terms from the term co-occurrence network, used this as a basis to quantify the three time-dimension characteristics of emerging technologies "past, present and future"——"fusion, novelty and potential scientific influence", used eigenvalues to filter whether technical topics were new or not, and built the emerging technology recognition model from the perspective of vector representation. Finally, taking the aviation field as an empirical study was to verify the scientific nature and rationality of the method. [Result/conclusion] Through the introduction of the computational perspective of "term vector representation", this paper effectively encoded the explicit and implicit associations between term entities, and improved the objectivity of feature calculation of emerging technologies; at the same time, combining historical, current and predicted technical information, this paper identifies them from two aspects of network structure and semantic features, and has been achieved good results.
Sun Mengge
,
Wang Yanpeng
,
Han Tao
,
Liu Panpan
. Research on Multi-Index Quantitative Recognition of Emerging Technologies: Exploration Based on Vector Representation Method[J]. Library and Information Service, 2022
, 66(3)
: 130
-139
.
DOI: 10.13266/j.issn.0252-3116.2022.03.014
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