Automatic Construction of EV Industry Chain Knowledge Graph based on Big Data
Yuhang Jia · 2023
The electric vehicle industry has seen a surge in demand for new energy sources in recent years, making it an attractive area for investment. However, for non-professional investors, it can be difficult to thoroughly analyze all the listed companies and identify investment opportunities without a clear understanding of the industry’s chain structure. In this study, we propose a new approach to building an industrial chain knowledge graph for the electric vehicle industry using big data and natural language processing techniques. These methods allow for the efficient and low-cost construction of an industrial chain system, making it more accessible to non-professional investors. We address the challenges of filtering relevant data from vast amounts of unstructured text data, dealing with diverse product names, and accurately identifying complex relationships in the industrial chain. By developing an ontology structure design and a multivariate relationship recognition model based on both text structural and semantic features, we are able to efficiently and accurately construct a comprehensive industrial chain system that can be used by non-professional investors to identify investment opportunities and make informed decisions.