基于多媒体分析的新特征融合对经济模型中会计投资决策方法的作用研究

Ping Wang
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引用次数: 0

摘要

会计投资分析一直在稳步发展,其中一些研究结果表明,投资者的限制性推理和自我心理情绪可能并不总能使他们的负面情绪影响他们的财务决策,从而导致亏损。由于电子商务和多媒体的发展,数字多媒体融合和显示成为可能,众多终端现在可以以无缝、实时的方式相互通信。本文提出了一种多媒体分析(MA)特征融合方法,用于了解网络零售环境中与会计投资相关的心理情绪,进而用于指导制定既适合目标人群又能取得成功的投资策略。这项研究的主要目标是展示多媒体信息的检索任务如何从文本预过滤与图像分类的结合中获益。在这项研究中,他们使用了可靠的中国股票市场与会计研究(CSMAR)数据库中的信息。支持本文调查的信息融合技术用于剖析实验结果、研究金融投资客户的情感效应问题以及评估本文的预期研究课题。在实验中,我们发现准确率达到了 97%。
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A study of the role of new feature fusion based on multimedia analysis on accounting investment decision methods in economic models

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.

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