Using Data Mining Approaches to Predict and Answer the Needs of Venture Capital

Nowadays the economy of developed countries work based on small and medium enterprises and knowledge-base industries. Researchers experimental findings indicate financing of small and medium enterprises and start-ups with innovative activities have heterogeneity and special characteristics to start a business. This heterogeneity and special characteristics of start-ups confront essential problems in financing for them.
Hence, for solving this problem, usage and continuity of venture capital process is necessary in order to encouragement and financing of innovative activities. Beside, in this process, venture capital firms in confrontation by pillar of financial markets need to conformity with the market regulations and policies. On the other hand venture capital firms in face of entrepreneurs and innovators confront challenges by how and state of ventures selection based on recognition and assessment of their risks for success or fail prediction of investments. The purpose of this research is response to this investors
challenges that lead investors to make superior evaluation and decision making in their start-ups investments through identification of the effective criteria on venture capital investments and their risk assessment for making trade-offs between them through multi criteria decision making method by usage of data mining and artificial intelligence.