Graph-Based Patent Mining for Mechanical Designs

Helal, Manal and Helal, Mohammed (2024) Graph-Based Patent Mining for Mechanical Designs. In: 14th International Conference on Electrical Engineering, 2024-05-21 - 2024-05-23, The Military Technical College.

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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.

Item Type	Conference or Workshop Item (Other)
Identification Number	10.1109/ICEENG58856.2024.10566338
Additional information	© 2024 IEEE. This is the accepted manuscript version of the paper which has been published in final form at https://doi.org/10.1109/TEM.2024.3422821
Keywords	patent mining, semantic analysis, graph data modelling, artificial intelligence, machine learning, big data analytics, similarity scoring, visualisation, functional analysis diagrams, simi-larity scoring, computer graphics and computer-aided design, artificial intelligence, control and optimization, energy engineering and power technology, electrical and electronic engineering, renewable energy, sustainability and the environment
Date Deposited	15 May 2025 16:50
Last Modified	04 Feb 2026 00:16