Title: Integration model of English teaching resources based on artificial intelligence
Authors: Yonggang Zhang; Danny Wang
Addresses: Oya International College, Henan University, Kaifeng, 475001, China ' Department of Electrical and Information Engineering, University of Cassino and South Latium, 03043, Cassino, Italy
Abstract: Aiming at the problems of low accuracy and high redundancy in the integration of teaching resources, an artificial intelligence-based model of English teaching resources integration is proposed. Web crawler recognition technology is used to obtain web page information of English teaching resources and to establish index database. L-NCD is introduced to eliminate redundant data of English teaching resources. ISPO algorithm and K-means algorithm are combined to complete the integration of English teaching resources and output results. The experimental results show that the resource integration accuracy of the model is higher than 90%, which proves that the resource integration accuracy of the model is higher. The resource repetition rate of this model is less than 1%, which proves that this model has a good effect of de-redundancy.
Keywords: resource integration; web crawler; K-means algorithm; English teaching.
International Journal of Continuing Engineering Education and Life-Long Learning, 2020 Vol.30 No.4, pp.398 - 414
Received: 13 Jun 2019
Accepted: 13 Aug 2019
Published online: 01 Nov 2020 *