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TRIZ分析矩阵智能构建方法研究 Research on Intelligent Construction Method of the TRIZ Analysis Matrix 作者：邢思思 1,2 钱力 1,2 作者单位： 1. 中国科学院文献情报中心北京 100190 2. 中国科学院大学经济与管理学院图书情报与档案管理系北京 100190 通讯作者：钱力 Email:qianl@mail.las.ac.cn 提交时间： 2022-06-09 摘要: [目的]基于深度学习和领域知识图谱技术，研究TRIZ分析矩阵自动构建方法，为技术创新提供知识支持。[方法]首先面向领域需求，将通用的技术要素延伸细化为实体和关系类别，完成领域知识图谱模式层设计；然后基于BERT预训练语言模型，研究设计从专利文献中自动识别知识实体及关系的智能化工具，实现实体关系自动抽取；最后利用图数据库完成领域知识图谱的构建，基于知识查询读取需要的知识实体和关系，实现TRIZ分析矩阵的自动构建。[结果]经实证验证，本文构建的面向薄膜磁头技术领域专利的BERT-MH+CRF实体识别模型F1分数为84.93%，BERT-MH+softmax关系抽取模型F1分数为63.7%。[局限]缺乏知识推理技术的应用，无法揭示实体间潜在的知识关联，构建的TRIZ分析矩阵的质量仍存在不足。[结论]所提出的方法可以实现TRIZ分析矩阵自动构建的目标，可以为技术创新提供有效的知识支持。 Abstract: [Objective] Based on deep learning and domain knowledge graph technology, study the automatic construction method of TRIZ analysis matrix to provide knowledge support for technological innovation. [Methods] First, facing the domain requirements, the general technical elements are extended and refined into entity and relationship categories, and the pattern layer design of domain knowledge graph is completed;Then, based on the BERT pre-trained language model, research and design an intelligent tool to automatically identify knowledge entities and relationships from patent documents, and realize the automatic extraction of entity relationships;Finally, the graph database is used to complete the construction of the domain knowledge graph, and the knowledge entities and relationships are required to read based on the knowledge query, so as to realize the automatic construction of the TRIZ analysis matrix. [Results] After empirical verification, the F1 score of the BERT-MH+CRF entity recognition model for patents in the field of thin-film magnetic head technology constructed in this paper is 84.93%, and the F1 score of the BERT-MH+softmax relation extraction model is 63.7%. [Limitations] The lack of application of knowledge reasoning technology cannot reveal the potential knowledge associations between entities, and the quality of the constructed TRIZ analysis matrix is still insufficient. [Conclusions] The proposed method can achieve the goal of automatic construction of TRIZ analysis matrix, which can provide effective knowledge support for technological innovation. TRIZ分析矩阵专利文献预训练技术实体识别关系抽取来自：邢思思分类：图书馆学、情报学 >> 情报学引用： ChinaXiv:202206.00104 (或此版本 ChinaXiv:202206.00104V1 ) doi:10.12074/202206.00104 CSTR:32003.36.ChinaXiv.202206.00104.V1 推荐引用方式：邢思思,钱力.(2022).TRIZ分析矩阵智能构建方法研究.中国科学院科技论文预发布平台.[ChinaXiv:202206.00104] 版本历史 [V1] 2022-06-09 01:23:01 ChinaXiv:202206.00104V1 下载全文

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