Research On Educational Resources Recommendation System Based On LBS On Wisdom Campus

With the rapid development of science and technology, the construction of wisdom campus has played an important role in educational reform. As an important part of the wisdom campus, personalized recommendation system aims to solve the problem of information overload. The recommendation system recommends some educational resources that students most likely to be interested in to them from mass information. A good education resources recommendation system is of great significance to improve students’academic performance, develop students’learning interest and improve the quality of education, which is an important goal of educational reform.Most of the traditional recommendation algorithms only consider the similarity be-tween the users and the content, no attention is paid to the user’s location information. However, in recent years, the mobile terminals and wireless networks spread quickly and indoor positioning technology has become increasingly mature. People can almost request service through network anywhere at any time, this change has made a great impact on the recommendation system. For example, in mobile environment, users may be interested in something temporarily because of their position. How to capture this temporary interest is an issue that is yet to be solved. Furthermore, in mobile environ-ment, users bring forward stricter real-time requirements to recommendation system. User’s interest is related to their position and the location of the users is always chang-ing, the recommendation system will not meet users’need if it runs slowly. In addition, the development of positioning technology makes it easier to obtain the users’location information for recommendation system. If the location information can be used scien-tifically and effectively, it can greatly improve the performance of the recommendation system. So, the development of these technologies is both an opportunity and a chal-lenge for the recommendation system.This paper focused on the construction of the educational resources recommen-dation system based on users’ location on wisdom campus. Firstly, this paper reviewed several traditional recommendation algorithms with their advantages and disadvantages analysed.Secondly, this paper presented a design of the infrastructure of education resources recommendation system and gave some reference scheme.Thirdly, considering the characteristics of the scenarios, this paper puts forward an improved recommendation algorithm which can solve the cold start problem and sparse matrix problem to a certain extent. Also, this algorithm runs faster than traditional algorithm with a better real-time performance. And it can capture the users temporary interest, too.Finally, some experiments were conducted on the datasets collected and Foursquare datasets. The experimental results have been analysed too.Experimental results show that the proposed algorithm have a better performance than traditional algorithm. It can meet the demand of the wisdom campus sense and have some reference values for other recommendation system in some similar scenarios.