Patents provide a rich source of information about design innovations. Patent mining techniques employ various technologies, such as text mining, machine learning, natural language processing, and ontology-building techniques. An automated graph data modelling method is proposed for extracting functional representations for building a semantic database of patents of mechanical designs. The method has several benefits: The schema-free characteristic of the proposed graph modelling enables the ontology it is based on to evolve and generalise to upper ontologies across technology domains and to specify lower ontologies to more specific domains. Graph modelling benefits from enhanced performance of deep queries across many levels of relationships and interactions and provides efficient storage. Graph modelling also enables visualisation libraries to use the graph data structure immediately, avoiding the need for graph extraction programs from relational databases. Patent/Design comparisons are computed by search queries using counting of overlaps of different levels and weights. This work has produced the PatMine SolidWorks Add-in \c{opyright}, which compares annotated CAD designs with patents and highlights overlapping design concepts. The patent annotation extracts its functional analysis, representing its structure as geometric feature interactions. Additional features such as full-text search and semantic search of the PatMine patents database are available, and graph analytic methods and machine learning algorithms are enabled and can be implemented as plug-ins in future work. Keywords: Patent Mining; Semantic Analysis; Functional Analysis Diagrams; Graph Data Modelling; Visualisation; Similarity Scoring; Big Data Analytics; Machine Learning; Artificial Intelligence; Natural Language Processing

翻译：专利提供了设计创新的丰富信息源。专利挖掘技术综合运用了文本挖掘、机器学习、自然语言处理和本体构建等多种技术手段。本文提出一种自动化图数据建模方法，用于提取功能表征以构建机械设计专利的语义数据库。该方法具有多重优势：所提出的图建模无模式特性使其所依托的本体能够演进并泛化至跨技术领域的高级本体，同时可向下细化为面向特定领域的低级本体。图建模在跨多层级关系与交互的深度查询中展现出增强性能，并提供高效的存储能力。此外，图建模使可视化库能够直接利用图数据结构，避免了从关系数据库中提取图数据的程序需求。专利/设计对比通过基于不同层级与权重的重叠计数进行搜索查询计算。本研究开发了PatMine SolidWorks插件\c{opyright}，该工具可将标注后的CAD设计与专利进行对比，并高亮显示重叠的设计概念。专利标注提取其功能分析结果，并将结构表征为几何特征交互。PatMine专利数据库还提供全文检索与语义搜索等附加功能，同时支持图分析方法与机器学习算法，这些功能可在未来工作中以插件形式实现。关键词：专利挖掘；语义分析；功能分析图；图数据建模；可视化；相似度评分；大数据分析；机器学习；人工智能；自然语言处理