Study on abnormal behaviour recognition of MOOC online English learning based on multi-dimensional data mining

In order to overcome the problems of low recognition accuracy and long recognition time of traditional English learning abnormal behaviour recognition methods, this paper proposes MOOC online English learning abnormal behaviour recognition method based on multi-dimensional data mining. Firstly, set up the multi-dimensional association item set of MOOC online English learning behaviour, mine the learning behaviour data for correction. Secondly, students' MOOC online English learning behaviour characteristics are extracted from students' target contour and blinking behaviour characteristics. Then, taking this as the training sample subset, the individual member classifier is constructed by the mixed perturbation method to classify the learning behaviour. Finally, the abnormal behaviour identification of MOOC online English learning is completed. The experimental results show that the proposed method has high accuracy and short recognition time.