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2025 | OriginalPaper | Chapter

Research on Disruptive Technology Prediction Methods Based on BERT Model and Graph Theory Analysis

Authors : Zhongyou Wang, Jianhui Zhang, Rongjian Li, Xiangdong Guo

Published in: World Conference of AI-Powered Innovation and Inventive Design

Publisher: Springer Nature Switzerland

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Abstract

The chapter delves into the prediction of disruptive technologies using the BERT model and graph theory analysis. It highlights the integration of patent analysis, bibliometrics, and expert systems to capture the intricacies of disruptive technology integration. The methodology involves constructing undirected weighted graphs, applying community detection algorithms, and employing a comprehensive scoring formula to identify potential disruptive technologies. The study also innovatively applies TRIZ theory for model construction and optimization, providing a robust framework for early detection and strategic planning of disruptive technologies.
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previous chapter Enhancing TRIZ Contradiction Resolution with AI-Driven Contradiction Navigator (AICON)
next chapter Research on the Identification and Analysis of Technological Opportunities Utilizing the BERT Model and MULTIMOORA Approach
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Metadata
Title
Research on Disruptive Technology Prediction Methods Based on BERT Model and Graph Theory Analysis
Authors
Zhongyou Wang
Jianhui Zhang
Rongjian Li
Xiangdong Guo
Copyright Year
2025
Book
World Conference of AI-Powered Innovation and Inventive Design

Print ISBN: 978-3-031-75918-5

Electronic ISBN: 978-3-031-75919-2

Copyright Year: 2025

DOI
https://doi.org/10.1007/978-3-031-75919-2_7

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