Abstract
In the context of the rapid development of computer technology, the level of informatization in various industries and fields is also rapidly increasing. In recent years, the scale of big data has continued to expand and has become the backbone of financial venture capital. The market volatility and business complexity brought about by Internet finance have challenged traditional economics and finance research paradigms. This article mainly introduces the application value research of big data mining technology in the field of financial risk investment. This paper uses data mining technology in big data to detect real-time dynamics in the field of financial risk investment and establish an early warning model. The model is solved by the decision tree algorithm, and the data is mined using the typical C4.5 algorithm in the decision tree algorithm to generate a decision tree and transform it into classification rules. Then discover the laws hidden behind financial risk investment to provide a reliable basis for financial investment. The experimental results in this paper show that the decision tree algorithm reduces the occurrence of financial investment risks by 18%, and performs early warning analysis of financial risks. Finally, based on big data, relevant technical analysis is carried out for the financial investment field.
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Yang, H. (2021). Application Value of Big Data Mining Technology in the Field of Financial Venture Capital. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 81. Springer, Cham. https://doi.org/10.1007/978-3-030-79197-1_48
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DOI: https://doi.org/10.1007/978-3-030-79197-1_48
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