The identification of emerging technologies (ETs) is pivotal for advancing technological innovation. However, current methods fail to sufficiently clarify ETs' innovation mechanisms and lack a consistent perspective to integrate the five attributes proposed by Rotolo. This paper presents an innovative term-level framework to identify and comprehend ETs through the perspective of technological knowledge flow (TKF). By dissecting TKF comprehensively, encompassing aspects of knowledge absorption, growth, and diffusion, we construct and explicate multidimensional indicators reflective of ETs' attributes, including relatively rapid growth, radical novelty, coherence, prominent impact, as well as uncertainty and ambiguity. Through the analysis of digital medical patent dataset, our framework proves effective in assessing emergent scores and pinpointing ETs with specificity at the term level, clarifying their technological components and efficacy. This is beneficial for technology developers to overcome technical difficulties and strategic decision makers to manage IP for competitive advantage.

新兴技术（ET）的识别对于推进技术创新至关重要。然而，当前的方法未能充分阐明ET的创新机制，并且缺乏一致的视角来整合Rotolo提出的五个属性。本文提出了一个创新的术语级框架，通过技术知识流（TKF）的角度来识别和理解ET。通过对TKF的全面剖析，涵盖知识吸收、增长和扩散等方面，我们构建并阐述了反映ET属性的多维指标，包括相对快速的增长、激进的新颖性、连贯性、显着的影响以及不确定性和模糊性。通过对数字医疗专利数据集的分析，我们的框架被证明可以有效地评估新兴分数并在术语级别精确定位具有特异性的 ET，阐明其技术组成和功效。这有利于技术开发商克服技术难点，有利于战略决策者管理知识产权以获得竞争优势。