The effective use of artificial intelligence in patent searches: A case study in using AI-based classifiers to identify AI inventions

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Aleksei L. Kalinichenko, Kelvin W. Willoughby
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引用次数: 0

Abstract

This study proposes a new patent search methodology for enhancing the quality and utility of patent research. The methodology focuses on techniques for effectively searching large patent datasets using artificial intelligence (AI) based classifiers to generate robust and reproducible results for subsequent statistical analysis. An extensive literature review revealed that salient approaches to patent searching fail to provide transparent, accurate and reproducible results, thereby hindering validation as well as evoking the need for manual post-processing and subjective judgments. Our proposed methodology, to enable precise, reliable and reproducible AI-enabled search queries, involves employing a novel terminological framework and formulating search regulations based on a formal definition of the technological subject matter of interest. We tested the methodology by applying it to patent searches in the field of AI technologies. In other words, we employed AI to facilitate our development of an operational technical definition of AI for patent searches. The primary results of our research are: (1) an automated patent search technique utilizing a learning algorithm guided by a formal definition of the search area; and (2) a novel terminological framework tailored for patent searches in the AI technology domain. Our approach offers enhanced transparency, reproducibility, and reliability in patent research, with applicability to both AI and other fields of technology.
人工智能在专利检索中的有效应用:使用基于人工智能的分类器识别人工智能发明的案例研究
本研究提出了一种新的专利检索方法,以提高专利研究的质量和实用性。该方法侧重于使用基于人工智能(AI)的分类器有效搜索大型专利数据集的技术,以生成鲁棒性和可重复的结果,用于后续的统计分析。一项广泛的文献综述表明,专利检索的主要方法无法提供透明、准确和可重复的结果,从而阻碍了验证,并引发了人工后处理和主观判断的需要。为了实现精确、可靠和可重复的人工智能搜索查询,我们提出的方法包括采用一种新的术语框架,并根据感兴趣的技术主题的正式定义制定搜索规则。我们通过将其应用于人工智能技术领域的专利检索来测试该方法。换句话说,我们利用人工智能来促进我们对专利检索人工智能的操作技术定义的开发。本研究的主要成果有:(1)利用一种以搜索区域的正式定义为指导的学习算法的自动专利检索技术;(2)为人工智能技术领域的专利检索量身定制的新术语框架。我们的方法在专利研究中提供了更高的透明度、可重复性和可靠性,适用于人工智能和其他技术领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
World Patent Information
World Patent Information INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.50
自引率
18.50%
发文量
40
期刊介绍: The aim of World Patent Information is to provide a worldwide forum for the exchange of information between people working professionally in the field of Industrial Property information and documentation and to promote the widest possible use of the associated literature. Regular features include: papers concerned with all aspects of Industrial Property information and documentation; new regulations pertinent to Industrial Property information and documentation; short reports on relevant meetings and conferences; bibliographies, together with book and literature reviews.
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