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Development of a fundamental patent exploration methodology based on technology knowledge flowopen access

Authors
Song, YoungchulKim, SunhyeYoon, Byungun
Issue Date
Nov-2025
Publisher
Springer-Verlag GmbH Germany
Keywords
Fundamental Patent Identification; Semantic Patent analysis; Patent Network Analysis; Technology Knowledge Flow
Citation
EPJ Data Science, v.14, no.1
Indexed
SCIE
SSCI
SCOPUS
Journal Title
EPJ Data Science
Volume
14
Number
1
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/62205
DOI
10.1140/epjds/s13688-025-00598-y
ISSN
2193-1127
2193-1127
Abstract
This study proposes a methodology for identifying fundamental patents based on their technical content. To overcome the limitations of existing methods that rely on citation networks and bibliographic information, this study extracts the subject-action-object (SAO) structure from patent claims to define the technical knowledge flow. A technical knowledge network is then constructed by identifying technical problems through modularity analysis. Fundamental patents are assessed using five characteristics: pioneering nature, applicability, originality, marketability, and path-dependency within the network. The fundamental patent is identified by calculating a fundamental score through entropy-based weights. A case study of CO2 capture technology and wearable watch technologies demonstrates that this approach can more accurately identify fundamental patents from a technical and problem-solving perspective compared to traditional methods. Notably, the methodology effectively tracks the foundation of technological innovation by reflecting the semantic flow between technical problems and their solutions. This study integrates and redefines the characteristics of fundamental patents, overcoming the limitations of previous patent analysis by reducing dependence on expert input by classifying technical problems and analyzing technical knowledge flow. This methodology highlights how rapidly growing patent data can be effectively analyzed to identify fundamental patents, contributing to R&D strategy and technology management decision-making.
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College of Engineering (Department of Industrial and Systems Engineering)
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