WEB-based Collaborative Platform for College English Teaching

At present, colleges and universities are trying to apply online education. The online college English course teaching cooperation platform is an important part of college English teaching. At present, teachers' scoring method for students' online examination on this kind of platform is mainly human scoring, which has a low efficiency. In view of this, based on the characteristics of web, this paper constructs an English test paper scoring algorithm based on text matching degree algorithm and improved KNN algorithm. The data analysis type of the algorithm is mainly prescriptive analysis that is, judging whether to give points according to the characteristics of the data. The automation and high efficiency of the algorithm can save a lot of human costs in the field of online education. The experimental results show that the recall rate of the improved KNN scoring algorithm for specific semantic topics is up to 0.9, and only 7.3% of students report that the algorithm misjudges their grades. The results indicate that the algorithm has the potential to be applied to the Web-based college English course teaching collaboration platform and reduce the workload of teachers and improve their efficiency.