Graph-Based Patent Mining for Mechanical Designs

Abstract

Patents represent a rich source of design innovations, prompting the application of different technologies. Machine learning, text and data mining, similarity scoring, and evolving ontology methods are among the various approaches applied in the literature. This study introduces a schema-free graph data modelling of Functional Analysis Diagrams (FAD) extracted from Patents and their associated Auto-CAD models. It aims to represent mechanical design patents semantically. The schema-free graph model allows for a flexible evolving ontology of known geometries, interactions, and functions. This evolution enables comprehensive queries and ensures efficient storage that is compatible with visualisation libraries.