基于IRGAN模型的外语教学资源自动推荐方法

Automatic Recommendation Method of Foreign Language Teaching Resources Based on IRGAN Model

针对当前外语教学资源推荐方法存在资源推荐效果较差、覆盖率和用户满意度较低的问题,提出了基于IRGAN模型的外语教学资源自动推荐方法。根据用户注册信息,制定外语教学资源推荐工作流程。在B/S模式的基础上,构建外语教学资源推荐的功能架构。采用IRGAN模型,结合生成检索模型,生成可推荐的外语教学资源。利用判别检索模型,挑选出重要度高的外语教学资源,生成推荐列表,构建外语教学资源自动推荐算法模型,实现资源自动推荐。实验结果表明,所提方法的外语教学资源推荐效果较好,能够有效提高外语教学资源推荐覆盖率和用户满意度。

Aiming at the problems of poor resource recommendation effect,low coverage and low user satisfaction in the current foreign language teaching resource recommendation methods,an automatic recommendation method of foreign language teaching resources based on the IRGAN model is proposed.According to the user registration information,formulate the workflow of foreign language teaching resource recommendation.On the basis of the B/S model,this paper constructs the functional framework of foreign language teaching resource recommendation.Irgan model and generative retrieval model are used to generate recommendable foreign language teaching resources.By using the discriminant retrieval model,the foreign language teaching resources with high importance are selected,the recommendation list is generated,and the automatic recommendation algorithm model of foreign language teaching resources is constructed to realize the automatic recommendation of resources.The experimental results show that the proposed method has a good effect on the recommendation of foreign language teaching resources,and can effectively improve the recommendation coverage and user satisfaction of foreign language teaching resources.