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Design And Development Of Internet + Tennis Training Service System

Posted on:2020-05-04Degree:MasterType:Thesis
Country:ChinaCandidate:Q X FangFull Text:PDF
GTID:2427330620955990Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
The existing tennis training method is of high price and low efficiency.Based on the "Internet +" operation mode,the tennis training service system is put forward,which realizes the remote teaching of tennis through the voice video technology,breaks through the time and space constraints,so as to improve the training efficiency and reduce the training price,and promote the better development and popularization of tennis.According to the demand analysis of Internet + tennis training service system,MySQL database management system is adopted to develop the system server side with the help of SSM development framework.The main functional modules of mobile client APP are designed and developed according to system requirements.The recommendation algorithm is used to realize the user personalized coach recommendation.The existing problems of the traditional user-based collaborative filtering algorithm are analyzed,an improved data filling method is proposed to solve the problem of data sparsity,and a time decay function is introduced to solve the problem of user interest transfer.The improved MAE algorithm is smaller and more accurate.In view of the low accuracy of user-based collaborative filtering algorithm in the case of high data sparsity,the svd-based collaborative filtering algorithm is introduced,and the MoviesLens data set is adopted for the comparison experiment of the two algorithms.The experiment proves that the MAE algorithm based on SVD is smaller and has higher accuracy.Finally,collaborative filtering algorithm based on SVD is selected as the recommendation algorithm of the system.Finally,this article carries on the function test to each function module,through the test entire system function basic realization.
Keywords/Search Tags:Internet plus, Server, database, collaborative filtering, SVD
PDF Full Text Request
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