基于大语言模型的专利关键词提取  

Patent Keyword Extraction Based on Big Language Model

作　　者：张彧烜 ZHANG Yuxuan(Chongqing University of Posts and Telecommunications Chongqing,400000)

机构地区：[1]重庆邮电大学,重庆400000

出　　处：《长江信息通信》2025年第2期68-71,共4页Changjiang Information & Communications

摘　　要：文章探讨了基于大语言模型的专利关键词提取方法。近年来,大语言模型如ChatGPT等在自然语言理解和生成任务上展现出强大的能力。该文提出了一种基于大语言模型的专利关键词提取方法,利用大语言模型的语义理解能力以及对专利文档的细致分析,实现了高效准确的关键词提取。实验结果表明,该方法在中文专利关键词提取任务中取得了显著的效果,为专利信息管理和分析提供了新的思路和方法。该文的研究对于解决海量专利文献的关键信息提取问题具有重要意义,为专利数据处理和分析提供了新的途径。未来的研究可以进一步探索大语言模型在其他领域的应用,并优化关键词提取算法以提高准确性和效率。This article explores a patent keyword extraction method based on the big language model.In recent years,large language models such as ChatGPT have demonstrated powerful capabilities in natural language understanding and generation tasks.The paper proposes a patent keyword extraction method based on the big language model,which utilizes the semantic understanding ability of the big language model and the detailed analysis of patent documents to achieve efficient and accurate keyword extraction.The experimental results show that this method has achieved significant results in the task of extracting Chinese patent keywords,providing new ideas and methods for patent information management and analysis.The research in this paper is of great significance for solving the problem of extracting key information from massive patent literature,and provides a new approach for patent data processing and analysis.Future research can further explore the application of big language models in other fields and optimize keyword extraction algorithms to improve accuracy and efficiency.

关 键 词：抽取 大语言模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]