面向TRIZ的专利技术三元组抽取研究与应用  

Extracting Triplets of Technology Patents for TRIZ

作　　者：刘春江[1] 李姝影[1] 方曙[1] 胡正银[1,2] 钱力 Liu Chunjiang;Li Shuying;Fang Shu;Hu Zhengyin;Qian Li(National Science Library(Chengdu),Chinese Academy of Sciences,Chengdu 610299,China;Department of Information Resources Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190,China;National Science Library,Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]中国科学院成都文献情报中心,成都610299 [2]中国科学院大学经济与管理学院信息资源管理系,北京100190 [3]中国科学院文献情报中心,北京100190

出　　处：《数据分析与知识发现》2024年第6期158-167,共10页Data Analysis and Knowledge Discovery

基　　金：国家社会科学基金项目(项目编号:19BTQ088);中国科学院2020年度西部之光人才项目(项目编号:E1C0000201);中国科学院青年创新促进会(项目编号:2022173)的研究成果之一。

摘　　要：【目的】针对专利技术三元组自动抽取的准确性和效率不高的问题,研究专利技术三元组抽取的模型,以提升个性化、细粒度、多维度的深度抽取与语义关联的准确性。【方法】针对技术问题、解决方案、技术功能与技术效果等4个技术主题维度,提出基于WeakLabel-Bert-BiGRU-CRF模型的抽取方法,使用宏平均等指标进行模型评估。【结果】选择石墨烯能量存储应用领域专利作为数据集,实验结果表明,相比于Bert-BiGRU-CRF模型,所提模型针对三元组抽取的宏平均超过0.8,进一步减轻了数据标注的工作量,抽取效果更好。【局限】所提模型需要领域专家和专利情报分析人员共同参与数据标注,标注质量的不同会对应用效果产生影响。【结论】基于WeakLabel-Bert-BiGRU-CRF模型,研建对应的原型系统,以便后续进一步使用与推广专利技术三元组抽取方法,在科技文献知识挖掘领域也有较广泛的应用前景。[Objective]This paper proposes a model for extracting patented technology triplets.It tries to improve the accuracy of personalization,fine-grained,multi-dimensional deep extraction,and semantic association.[Methods]We constructed an extraction method based on the WeakLabel-Bert-BiGRU-CRF model for four technical dimensions:problems,solutions,functions,and effects.We evaluated the model using indicators such as the macro average.[Results]We examined the new model with patents in graphene energy storage applications.Compared to the Bert-BiGRU-CRF model,the proposed method achieved a macro average of over 0.8 for triplet extraction and reduced the workload of data annotation.[Limitations]The proposed model requires domain experts and patent analysts in data annotation,and annotation quality affects application effectiveness.[Conclusions]The proposed model could effectively extract patent technology triplets,which has a broad application prospect in scientific literature knowledge mining.

关 键 词：TRIZ 三元组抽取 专利技术 WeakLabel-Bert-BiGRU-CRF 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] G250[自动化与计算机技术—计算机科学与技术]