Big Data-Driven Scientific and Technological Innovation Mechanism Optimization and Decision Support System

The purpose of this study is to explore the mechanism optimization and decision support system of science and technology innovation driven by big data, especially the application of open innovation and data mining technology in it. In the current rapidly developing information age, big data has become an important driving force to promote scientific and technological innovation. By combining big data analysis, open innovation and data mining technologies, this study designed an efficient decision support system to optimize the scientific and technological innovation system and provide strong support for decision makers. The system makes full use of the deep mining and analysis capabilities of big data, integrates resources of all parties through an open innovation platform, and promotes cross-border cooperation and knowledge sharing. The system collects data related to scientific and technological innovation through various channels to provide high-quality data basis for subsequent analysis. With the ability of self-learning and optimization, it can constantly adjust and improve the algorithm model according to user feedback and actual operation effect, and improve the accuracy and adaptability of decision support. This system will help improve the efficiency and quality of scientific and technological innovation, reduce decision-making risks, and provide strong support for innovation entities such as governments, enterprises and scientific research institutions. At the same time, this study also shows the broad application prospects of big data and open innovation in the field of scientific and technological innovation, which provides a strong guarantee for promoting the development of scientific and technological innovation in our country.