Optimization of Business Model of Digital Economy Platform based on Computer Algorithm

In response to the problems of low efficiency and single profit model of digital economic platforms in market competition, this paper constructs a big data platform containing multi-dimensional data such as user behavior. Then, the collaborative filtering algorithm is used to analyze user needs, consumption habits and their changing trends, and generate an accurate recommendation system and a personalized advertising delivery model. In addition, an intelligent decision support system is designed, and the effect of the optimization model is verified through simulation experiments and the optimization algorithm is continuously iterated. In the 7th and 8th cycles, the efficiency increased from 86% and 85% to 92% and 91% respectively, reflecting the optimization effect of the intelligent decision-making system in resource allocation and scheduling. The research results of this paper help the platform achieve accurate operation and sustainable development in a complex and changing market environment.