A study of the role of new feature fusion based on multimedia analysis on accounting investment decision methods in economic models

Abstract

Accounting investing analysis has been expanding at a steady clip, and some of the findings suggest that investors' restricted reasoning and self-psychological sentiments may not always lead them to make their negative emotions influence their financial decisions, leading to a loss. Digital multimedia fusion and display are made possible, and numerous terminals may now communicate with one another in a seamless, real-time manner thanks to the growth of e-commerce and multimedia. This paper proposes a Multimedia Analysis (MA) feature fusion method for understanding the psychological emotions associated with accounting investments in the online retail environment, which can then be used to guide the development of an investment strategy that is both appropriate and successful for the target demographic. The primary goal of this study is to show how multimedia information retrieval tasks may benefit from combining text pre-filtering with image sorting. For this investigation; they used information from the reliable China Stock Market and Accounting Research (CSMAR) Database. The information fusion technology that supports this paper's investigation is used to dissect experiment outcomes, examine issues with the emotional effect of financial investment clients, and assess the paper's intended study topic. In experiments, we found a 97% accuracy rate in terms of accuracy.