Research on the dynamic evolution mechanism of disruptive technology based on the BERTopic model and Hidden Markov Model: A case study of industrial Internet technology
Heng Yang, Sheng Chen, Xin Yang
TL;DR
This paper studies how Industrial Internet technology has evolved over time using patent data and machine learning models to identify trends and development patterns.
Contribution
The novel use of BERTopic and Hidden Markov Models to analyze the dynamic evolution of Industrial Internet technologies through patent data.
Findings
Industrial Internet technologies are categorized into five layers, with the data layer being the most developed.
The physical layer is more developed than the logical and interaction layers.
The HMM model reveals evolutionary patterns in technological topics over time.
Abstract
The development of key technologies for the Industrial Internet is a major concern for countries worldwide. This paper aims to comprehensively understand the technology of the Industrial Internet by analyzing its current application status and trends. It will dynamically examine the key technologies and development trends of the Industrial Internet, providing a valuable reference for technological advancements in this field. This paper analyzed global patent data in the field of the Industrial Internet from 1965 to 2023. The paper applied the BERTopic model and the all-MiniLM-L6-v2 model to extract and vectorize topics related to industrial internet technology from patent texts. Based on the theory of Internet governance, the paper categorizes the topics into four categories. The paper then established the Hidden Markov Model (HMM) to investigate the evolutionary mechanism of…
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Taxonomy
TopicsDigital Transformation in Industry · Big Data and Digital Economy