Research on the Evolution of Textile Technology Theme Content Based on Entity Recognition

专利文本是技术创新的核心构建要素，对文本内容进行主题分析有助于厘清技术主题分布及演变趋势。以2018~2022年间知网纺织面料制备技术专利为研究对象，利用命名实体识别进行研究，以提取物体类实体作为专利文本内容分析的依据，按年划分时间窗口，使用困惑度–主体方差得到最优主题数。通过分析技术主题内容演变过程总结得到纺织面料制备的创新模式。通过分析主题内容演变过程，将其归纳为面料原料、面料制备工艺和面料特性三组技术元素，给出进一步面料制备的开发建议。为了克服主题建模中难以准确快速地选定词簇表示主题的难题，利用命名实体识别技术简化技术术语抽取工作，使用ERNIE3.0知识增强预训练模型快速得到具备强概括能力的技术术语集合。Patent text is the core building element of technological innovation, and thematic analysis of text content is helpful to clarify the distribution and evolution trend of technological themes. Taking CNKI textile fabric preparation technology patents from 2018 to 2022 as the research object, Named-entity recognition was used for research, and object-like entities were extracted as the basis for patent text content analysis. Time windows were divided by year, and the optimal number of topics was obtained using Perplexity subject variance. Summarize the innovative mode of textile fabric preparation by analyzing the evolution process of technical theme content. By analyzing the evolution process of the theme content, it is summarized into three technical elements: fabric raw materials, fabric preparation process, and fabric characteristics, and further development suggestions for fabric preparation are provided. In order to overcome the difficulty of accurately and quickly selecting word clusters to represent topics in topic modeling, Named-entity recognition technology is used to simplify the extraction of technical terms, and ERNIE3.0 knowledge enhancement pre-training model is used to quickly obtain technical term sets with strong generalization ability.