Graph-Based Patent Mining for Mechanical Designs

Manal Helal; Mohammed Helal

doi:10.1109/ICEENG58856.2024.10566338

Graph-Based Patent Mining for Mechanical Designs

Manal Helal, Mohammed Helal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

23 Downloads (Pure)

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.

Original language	English
Title of host publication	ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering
Subtitle of host publication	ICEENG-14
Place of Publication	Cairo, Egypt
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	6
ISBN (Electronic)	9798350343427
ISBN (Print)	979-8-3503-4342-7
DOIs	https://doi.org/10.1109/ICEENG58856.2024.10566338
Publication status	Published - 25 Jun 2024
Event	14th International Conference on Electrical Engineering - The Military Technical College, Cairo, Egypt Duration: 21 May 2024 → 23 May 2024 Conference number: 14 https://iceeng.conferences.ekb.eg/

Publication series

Name	ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering

Conference

Conference	14th International Conference on Electrical Engineering
Abbreviated title	ICEENG-14
Country/Territory	Egypt
City	Cairo
Period	21/05/24 → 23/05/24
Internet address	https://iceeng.conferences.ekb.eg/

Keywords

Patent Mining
Semantic Analysis
Graph Data Modelling
Artificial Intelligence
Machine Learning
Big Data Analytics
Similarity Scoring
Visualisation
Functional Analysis Diagrams
Simi-larity Scoring

Access to Document

10.1109/ICEENG58856.2024.10566338Licence: Unspecified

Accepted_Manuscript
© 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
Accepted author manuscript, 890 KBLicence: CC BY

Cite this

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title = "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.",

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note = "{\textcopyright} 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; 14th International Conference on Electrical Engineering, ICEENG-14 ; Conference date: 21-05-2024 Through 23-05-2024",

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series = "ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering",

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Helal, M & Helal , M 2024, Graph-Based Patent Mining for Mechanical Designs. in ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering: ICEENG-14. ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering, Institute of Electrical and Electronics Engineers (IEEE), Cairo, Egypt, 14th International Conference on Electrical Engineering, Cairo, Egypt, 21/05/24. https://doi.org/10.1109/ICEENG58856.2024.10566338

Graph-Based Patent Mining for Mechanical Designs. / Helal, Manal; Helal , Mohammed.
ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering: ICEENG-14. Cairo, Egypt: Institute of Electrical and Electronics Engineers (IEEE), 2024. (ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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KW - Semantic Analysis

KW - Graph Data Modelling

KW - Artificial Intelligence

KW - Machine Learning

KW - Big Data Analytics

KW - Similarity Scoring

KW - Visualisation

KW - Functional Analysis Diagrams

KW - Simi-larity Scoring

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T3 - ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering

BT - ICEENG 2024 - 14th IEEE International Conference on Electrical Engineering

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Cairo, Egypt

T2 - 14th International Conference on Electrical Engineering

Y2 - 21 May 2024 through 23 May 2024

ER -

Graph-Based Patent Mining for Mechanical Designs

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Keywords

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