With the assistance of digital media, entertainment oriented E-learning models can effectively enhance students' learning enthusiasm. This article analyzes the application of entertainment E-learning mode based on Apriori algorithm in intelligent English reading assistance mode. At present, English reading teaching faces some problems, such as outdated teaching methods, passive learning among students, excessive emphasis on imparting grammar knowledge while neglecting the improvement of students' reading skills and strategies, and so on. Therefore, this article conducts research on intelligent English reading comprehension tools based on semantic analysis and Apriori algorithm. This paper proposes a recreational E-learning model based on Apriori algorithm. Based on Apriori algorithm, students' interests and preferences on different learning resources and entertainment elements are mined and incorporated into the learning model design. Then, a set of entertaining English reading assistant model is designed, which uses a variety of entertainment elements, such as gamified learning, interactive activities and reward mechanism, to increase students' learning participation and enthusiasm. This article adopts the idea of LSA algorithm to construct a BERT semantic analysis model. We treat nodes in the network as word items and then use singular value decomposition algorithm to decompose the word document matrix. Secondly, the original association rule Apriori algorithm was optimized, and the optimized association rule Apriori algorithm effectively solved the problem of excessive computation in traditional algorithms. Finally, based on semantic analysis and Apriori algorithm, this article designs an intelligent English reading comprehension tool, mainly analyzing the practical application of the system and greatly improving the efficiency of English reading teaching.
