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| Identifying Emerging Technology with LDA Model and Shared Semantic Space——Case Study of Autonomous Vehicles |
Zhou Yunze,Min Chao( ) |
| School of Information Management, Nanjing University, Nanjing 210023, China |
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Abstract [Objective] The paper proposed a new method to identify emerging technologies using shared semantic model and multi-source data. [Methods] We used the LDA model to detect the topics of multi-source data. Then, we utilized the Word2Vec model to create vectors for these topics based on the representative words and their weights. Third, we merged the topics, and used topic strength and novelty to identify emerging technologies. [Results] We found seven emerging technoligies from the field of Autonomous Vechicles, including Driver Switching, Selection and Control of Travel Path, Lane Change Safety, Motion Estimation and Risk Aversion, Structure Design, Perception of the Environment, as well as Communication Technology and Communication Security. [Limitations] More research is needed to explore better ways to determine the threshold and find fine-grained topics. [Conclusions] The proposed method is able to detect emerging topics using data from multiple sources, which optimizes the exisiting methods.
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Received: 28 August 2021
Published: 14 April 2022
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| Fund:Social Science Fund of Jiangsu Province(18TQC005);Fundamental Research Funds for the Central Universities(14380005) |
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Corresponding Authors:
Min Chao,ORCID：0000-0002-0627-995X
E-mail: mc@nju.edu.cn
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