Data Mining of English Language Instructional System Based on Improved Collaborative Filtering Algorithm

Abstract

The use of computer-aided language learning (CALL) in practical teaching has built an interactive platform for the integration of computer and language teaching. In order to solve the problem of data sparseness in the information recommendation model of English resource database with large data volume, this article proposes a data mining (DM) in database (KDD) model of CALL system based on improved CF algorithm. Through CF algorithm and the expression of resource feedback matrix, the resource selection is realized. The results show that the algorithm has high recommendation accuracy and time complexity. The model algorithm has high recommendation accuracy and efficiency, which effectively solves the problem of large data sparseness, can further enhance the effect of computer-aided instruction (CAI) system, improve the classroom experience of educators and learners, and promote the intelligent growth of CAI system.