Visualization System Of Intelligent Abstract And Risk Grading Based On Institutional Entities

(1) Investigate the principles and existing methods of financial risk management, analyze the pain points of financial risk control business at the current stage, examine the detailed requirements of credit information companies and credit institutions on public opinion data, then combine the theory and of sentiment analysis and intelligence abstracts and methods of data visualization to develop a reasonable and feasible solution.

(2)Sources of news released by reliable financial media and authoritative quality inspection departments are divided into different text structures through data preprocessing. After unstructured sentences are structured, different natural language processing methods are used to extract the risk information and comprehensively evaluate the results.

(3) According to data-driven, componentized development and separation of data and performance of the three core ideas, the overall design of the data visualization system and the overall implementation of the front-end and server-side, and focus on the data interaction and synchronization between the front and back end.