摘要
[研究目的]对人工智能专利进行检索是相关情报分析、实证研究的基础。该文结合现有检索方法,研究了人工智能专利的多层次框架式检索方案,以期提供全面、准确、噪音低且包含确定检索字段和检索语法的人工智能专利检索方案。[研究方法]对人工智能技术进行了系统的层级划分及各层级内容梳理,并根据各技术层级特点,采用关键词与分类号组合、关键词与关键词组合的方式,充分拓展关键词和分类号,强化对各类技术名词的研判,同时考虑噪音控制。[研究结论]人工智能专利多层次框架式检索方案具有灵活性高、适用性广的优点,最后给出相应的检索实例以供参考。
[Research purpose]The retrieval of artificial intelligence patents is the basis of relevant information analysis and empirical research.Based on the existing retrieval methods,a multi-level frame retrieval scheme for artificial intelligence patents is proposed in this paper,aim to provide a comprehensive,accurate,low noise artificial intelligence patent retrieval scheme,including the determinate search fields and search syntax.[Research method]The artificial intelligence technology is systematically divided into levels and the content of each level is sorted out,and according to the characteristics of each technical level,the combination of keywords and IPC classification number and combination of keywords and keywords are adopted.keywords and IPC classification number are fully extended,and the research and judgment of various technical terms is strengthened.Besides,noise control is considered.[Research conclusion]The scheme has the advantages of high flexibility and wide applicability.In the end of this paper,the corresponding retrieval examples are given for reference.
作者
李文红
唐春
Li Wenhong;Tang Chun(Shanghai International College of Intellectual Property,Tongji University,Shanghai 200092;School of Intellectual Property,East China University of Political Science and Law,Shanghai 201620)
出处
《情报杂志》
CSSCI
北大核心
2023年第9期172-178,共7页
Journal of Intelligence
关键词
人工智能
专利检索
人工智能技术
层次框架
多层次检索
artificial intelligence
patent retrieval
artifical intelligence
hierarchical framework
multi-level retrieval
作者简介
李文红,男,1978年生,博士研究生,研究方向:人工智能与知识产权;唐春,男,1976年生,博士,副教授,研究方向:专利管理。
