Discovering Technology Opportunities with Causal Knowledge: Case Study of EV Charging Stations
Liu Linlin1,2,Gong Daqing3(),Zhang Yujie4,Bai Rujiang4
1Institute of Artificial Intelligence and Big Data, Zibo Vocational Institute, Zibo 255314, China 2The Global Development Institute, The University of Manchester, Manchester M139PL, UK 3School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China 4Institute of Information Management, Shandong University of Technology, Zibo 255049, China
[Objective] This paper proposes a new method to identify technology opportunities from documents with the help of causal knowledge. [Methods] The proposed method includes three steps of automatic extraction of causal pairs, construction of causal network and discovery of matching tech-opportunities. Firstly, we used the rule matching method to automatically extract the causal pairs from multi-source data based on causal trigger words and rule templates. We also represented these pairs by triple structure. Then, we constructed the causal network including technical elements and found the demand factors in the process of use. Finally, we completed the potential causal correlation with the link prediction of causal network, which was matched with user demand factors and helped us discover tech-opportunities. [Results] We examined the proposed model with charging stations data of the EVs. We found the battery performance and charging costs are the key factors to improve technical performance and user experience. The GraphSAGE algorithm can more accurately predict the edge connection than Node2Vec, which effectively identify the potential technical opportunities. [Limitations] The accuracy of the proposed method needs to be improved. [Conclusions] The proposed method could effectively discover sci-tech innovation opportunities, as well as potential uncertain issues, which provides reference for further technology optimization and industry upgrading.
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Liu Linlin, Gong Daqing, Zhang Yujie, Bai Rujiang. Discovering Technology Opportunities with Causal Knowledge: Case Study of EV Charging Stations. Data Analysis and Knowledge Discovery, 2022, 6(8): 31-40.
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