Study on the Optimization of College English Teaching Evaluation System Based on DBSCAN Clustering Algorithm

In the new era with rapid development of information technologies, the research of designing and refining an assessment tool for professionals plays an extremely important role in the construction of a scientific evaluation system of College English teaching. However, the traditional Decision tree algorithm has some limitations in solving the problem of system simulation, especially when dealing with complex problems. This paper proposes a research scheme of designing and refining an assessment tool for professionals based on DBSCAN Cluster algorithm to better solve this problem. With DBSCAN Cluster algorithm, the research scheme can accurately locate the influencing factors through directly density-reachable theories, so as to determine the division of indicators reasonably, which will further reduce the interferences during the process. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional Decision tree algorithm in terms of research accuracy and processing time of the research influencing factors. Therefore, the simulation scheme based on DBSCAN Cluster algorithm in construction and optimization of College English teaching evaluation system can better break through the limitations of traditional Decision tree algorithm and improve the simulation accuracy and efficiency. Thus hopefully, this research will shed some light on promoting the innovation and development of technology as well as the efficiency of College English teaching.