Akademik Veri Yönetim Sistemi
2nd International Conference on Forthcoming Networks and Sustainability in the IoT Era (FoNeS-IoT), ELECTR NETWORK, 8 - 09 Ocak 2022, cilt.129, ss.174-181
With the widespread application of new technologies in the financial field, many new service models or companies have emerged in China. These new companies have transformed traditional financial service companies and have had a huge impact on the financial industry. Internet finance companies use mobile Internet, cloud computing, big data and other technologies to vigorously expand the fields of payment, lending, investment, asset management and other fields, and continue to expand applications and business fields, which has caused a lot of shock to the traditional financial sector. The purpose of this paper is to study the construction of a credit knowledge service model in the financial field based on the integrated SVM data stream classification algorithm. This paper establishes the construction of a credit knowledge service model in the financial field based on the integrated SVM data stream classification algorithm, and analyzes the specific content of the credit knowledge service in the financial field in detail. According to the experimental research in this article, the accuracy of financial data retrieval based on the integrated SVM data stream classification algorithm proposed in this article is very high. When the search result of the EASR algorithm of the flow classification algorithm is different from the detection result of the engine's own algorithm, the accuracy of the EASR algorithm is higher, reaching about 92.2%.