基于组合概率的技术主题新颖性研究

Examining Novelty of Technological Topics Based on Combination Probabilities

技术新颖性被认为是突破性创新的重要动力,全面衡量技术主题内容新颖性,有助于尽早识别新颖性专利并降低新兴关键技术延迟识别的风险。主题词作为技术的知识元之一,能很好地表征技术发明的主题内容和方法。本文提出一种从组合概率视角测度技术主题内容新颖性的方法,融合了专利主题词的直接组合次数、间接组合概率和语义相似度三个方面。以人工智能领域的发明专利为例,验证该方法能够捕捉主题词组合之间的潜在距离,比单一指标能够识别出更多新颖性组合。本文发现高新颖性/高常规性组合专利具有较高的平均被引次数,高新颖性专利成为高被引专利的概率最大。

Technological novelty is considered to be an important driving force to facilitate the breakthrough of innovation.Comprehensively measuring the novelty of technological topics can help identify novelty patents as early as possible and reduce the risk of delayed identification of emerging key technologies.As a knowledge element of technology,subject headings can adequately represent the subject content and methods of technological inventions.This study proposes a method to measure the novelty of technological topics from the perspective of combination probability,which integrates the direct combination times,indirect combination probability,and semantic similarity of patent subject words.Taking invention patents in the field of artificial intelligence as an example,it is verified that the method can capture the potential distance between subject word combinations,as well as identify more novelty combinations than a single indicator.The study’s findings indicate that high novelty/high conventional patents exhibit a higher average number of citations,and the high novelty patents exhibit the highest probability of becoming highly cited patents.