Effectiveness Analysis of Entrepreneurial Legal Risk Prevention Based on Multi-Modal Deep Learning Model

Author:

Li Tianhua1ORCID,Qu Shaowei1ORCID

Affiliation:

1. Department of Management Science and Engineering, School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China

Abstract

With the emergence of the upsurge of entrepreneurship, entrepreneurs are increasingly concerned about legal risks. In the process of entrepreneurship, legal risk is the biggest hidden danger of entrepreneurial enterprises. The prevention and avoidance of legal risks is a long and arduous process, and not all risks can be identified and avoided in time. The deep learning method has brought great changes to the fields of speech recognition, image recognition and natural language processing. The tasks in these fields only involve single-mode input, but more recent applications need to involve multi-mode intelligence. Multimodal deep learning mainly includes three aspects: multimodal learning representation, multimodal signal fusion and multimodal application. Through the research on the legal risks in recent years, this paper believed that there are many legal problems in the development of entrepreneurial enterprises, including contract disputes, trade secret disputes, trademark infringement disputes, copyright infringement disputes, etc. This paper aimed to study the problem of Legal Risks of Entrepreneurship (LRE) that entrepreneurs are concerned about, and proposed a new solution from the perspective of image recognition technology. 486 entrepreneurs were investigated by questionnaire. In the process of entrepreneurship, 87.04% of entrepreneurs encountered legal risks, and they would turn to lawyers for help, which is a better way. However, in most cases, entrepreneurs are exposed to LRE because of their insufficient understanding of economic law, so they solve it through lawyers. However, if a lawyer is hired, the cost would be very high, which would bring great economic pressure to the enterprise. Only 17.90% of entrepreneurs would safeguard their legitimate rights and interests through their own knowledge and legal weapons without resorting to lawyers. It can be seen that entrepreneurs have relatively low practical ability in the use of LRE, and their legal practical ability is obviously insufficient.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

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