Research On Personalized Recommendation System Of English Resources Based On Location Situation

Driven by modern information technologies such as Internet of Things,cloud computing,big data and artificial intelligence,China’s education informatization construction has developed rapidly,and it has clearly shown the characteristics of intelligence,personalization and socialization.Based on modern information technology,respecting students’ individualized learning and diversified development needs,creating intelligent education and learning environment and cultivating intelligent talents have become a new trend in the development of educational informatization.At the same time,with the rapid growth of resources,it has become a reality to provide learners with massive learning resources.However,the explosive growth of learning resources has brought convenience to learners,and at the same time,it has also produced practical problems that cannot be ignored,such as “resource overload” and “learning lost”.Therefore,how to make effective use of modern information technology,build an intelligent learning environment,provide intelligent learning services,and help learners screen out the required content from massive learning resources and complete recommendations is an important problem to be solved urgently in the current process of intelligent education construction.Starting from LBS(Location Based Services),this paper focuses on the application of intelligent education services based on the Internet of Things,and uses the advantages of personalized recommendation system in resource recommendation and the importance of English in the world at present to design and develop a personalized recommendation system for English resources based on location situation.Based on the idea of collaborative filtering,the system realizes resource recommendation according to the similar user resource scores of target users and the needs of target users.At the same time,the improved Wireless Sensor Network,WSN)positioning technology is used to obtain the user’s location situation information,and the location situation is combined with the user’s needs,so that the pushed resources can better meet the user’s needs and further improve the resource utilization rate and learning efficiency.The main research contents and achievements include:(1)In order to obtain more accurate user location information,aiming at the hot research problem of WSN location,combined with the application research of new intelligent computing technology,two novel WSN location algorithms are proposed successively.(1)Sparrow Search Algorithm,SSA)is introduced into the field of WSN location,and a Sparrow search based on localization algorithm(SSA＿LA)is proposed.This is the first attempt and exploration of sparrow search algorithm applied to WSN positioning field.(2)Combining the sparrow search algorithm with the classical centroid localization algorithm,and introducing the region estimation method,a sparrow search centroid location algorithm based on region estimation(SSCLA＿RE)is proposed.It can reduce the search space of feasible solution,speed up the search speed of the algorithm and effectively improve the positioning accuracy of the algorithm.Simulation experiments have verified the feasibility and effectiveness of the above two algorithms.(2)In order to push learning resources more accurately,the collaborative filtering recommendation technology based on location is studied,and the collaborative filtering recommendation algorithm based on location is proposed.Firstly,the user’s location situation information is clustered,and the neighboring users of the target user are obtained according to the clustering results;Secondly,the similarity between target users and neighboring users is calculated to obtain similar users;Then,the score value of the target user is predicted by the resource score of similar users,and the recommendation is made according to the score value;Finally,the feasibility of the algorithm is verified by experiments and recommended algorithm detection indicators.(3)Based on the above research results,a personalized recommendation system for English resources based on location situation is designed and implemented.The core function of the system is to recommend English learning resources based on users’ location.The test results show that the system can better match and recommend resources related to location situations,which can not only help learners to learn English better,but also help learners to automatically obtain situational communication sentences in different application scenarios,which shows high application value.