College English tutoring is an important content of current research, and how to provide more effective methods for teaching tutoring is currently a hot research topic. Therefore, this paper designs an Internet-based online tutoring platform for college English teaching, which is accelerated by using the K-means clustering algorithm. The data processing efficiency and processing methods to improve user satisfaction require more practical experience to summarize. In the business logic layer, the uploaded information is mined through the K-means clustering algorithm to form an online tutoring university English database to provide platform data support, realize the business logic judgment of the data, convert the data in the database, and return to the user interface of other formats, to provide users with browsing and consulting. In the data access layer, the data from the business logic layer is processed. After the processing is completed, data can be added, deleted, modified, and checked in the database. Finally, the operation result of the database is fed back to the business logic layer for processing. Experimental results show that the designed platform has good data mining performance, low connection speed and low response delay, good compatibility, low CPU usage, fast resource sharing speed, and high user satisfaction. It can be connected to different operating systems.