{"title":"Integrating Generative Artificial Intelligence techniques into technology function matrix analysis","authors":"Huei-Yu Wang , Shu-Hao Chang , Chia-Yi Chuang","doi":"10.1016/j.wpi.2025.102352","DOIUrl":null,"url":null,"abstract":"<div><div>This study proposes a novel method for automating the construction of technology-function matrices using generative artificial intelligence (GAI), specifically focusing on quantum technologies. By leveraging GAI to analyze International Patent Classification (IPC) definitions and benchmark reports, we developed a system that rapidly generates technology-function matrices, significantly reducing the time required for manual analysis. The method was applied to 2,399 quantum technology patents from 2023 to March 2024, covering four key areas: secure communications, computing, quantum simulators, and sensors. This approach not only aids government agencies in identifying new technological opportunities but also facilitates the industrialization of potential technologies. By combining GAI with established analytical frameworks, this study contributes to both the theoretical understanding and practical application of patent analysis in emerging fields.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"81 ","pages":"Article 102352"},"PeriodicalIF":2.2000,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Patent Information","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0172219025000195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This study proposes a novel method for automating the construction of technology-function matrices using generative artificial intelligence (GAI), specifically focusing on quantum technologies. By leveraging GAI to analyze International Patent Classification (IPC) definitions and benchmark reports, we developed a system that rapidly generates technology-function matrices, significantly reducing the time required for manual analysis. The method was applied to 2,399 quantum technology patents from 2023 to March 2024, covering four key areas: secure communications, computing, quantum simulators, and sensors. This approach not only aids government agencies in identifying new technological opportunities but also facilitates the industrialization of potential technologies. By combining GAI with established analytical frameworks, this study contributes to both the theoretical understanding and practical application of patent analysis in emerging fields.
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.