Analysis of Innovation Paths Big Data Mining to Big Data Algorithm of Business Administration

Abstract

In the process of enterprise management, there are some problems such as poor accuracy and long selection time of computer science innovation path, which seriously affect the effective selection of computer science path innovation. Based on a big data mining method, this paper analyzes the path innovation of computer science from three dimensions, constructs the path set of path innovation by least dichotomy, and obtains the optimal innovation path by derivation. Then, the maximum likelihood theory is used to calculate the innovation path and compared it with the previous path innovation methods, comparing the accuracy and calculation time of different innovation paths. MATLAB simulation results show that the big data mining method can improve the accuracy and comprehensiveness of innovation path selection, reaching more than 90%, and control the selection time of the innovation path within 25 seconds, and the overall result is better than the previous path innovation methods. Therefore, the big data mining method can improve the accuracy of computer science innovation path selection and meet the needs of computer science path innovation in business administration. However, in the research of big data mining methods, this paper ignores the analysis of multi-path innovation, which leads to insufficient research depth. In the future, it will further analyze multi-path innovation.