A method of Evaluation for Small and Medium-sized Enterprises

Abstract

Abstract-Small and medium-sized enterprises (SMEs) have characteristics of small scale of development, poor anti-risk ability, and imperfect management. Timely and accurate evaluation of these enterprises is of great significance to corporate management, market supervision departments and social investors. Existing evaluation methods are mostly based on the internal financial information of mature enterprises, which are not suitable for small and medium-sized enterprises which have not yet achieved revenue capabilities, and have imperfect financial indicators. In this paper, we propose an evaluation model of the development trend of SMEs based on the enterprise knowledge graph. We obtain the information of these enterprises on the financial websites and then use entity recognition and relationship techniques to explore major events and relationships between enterprises, and build enterprise knowledge graph. We construct the feature sets of these enterprises, and use cluster analysis to classify and evaluate the enterprises. A graph-based neural network method is proposed to capture the deeper influence on the development trend among enterprises. The proposed method evaluates the development trend of SMEs from a new perspective.