{"title":"Research on Mobile Point Exchange System Based on Collaborative Filtering Recommendation Algorithm","authors":"Le Feng, Zehui Mu","doi":"10.21307/ijanmc-2021-018","DOIUrl":null,"url":null,"abstract":"Abstract This paper describes the development process of the mobile point exchange system from demand analysis, outline design, detailed design and implementation. The system combines current business needs and uses collaborative filtering recommendation algorithms to solve the problem of how to calculate data similarity. The system is written in JAVA language, and uses a layered architecture model to separate business modules and functional modules. The front-end uses HTML, FreeMarker and Vue technologies to achieve page display and data rendering, and the persistence layer framework uses Mybatis to implement customized SQL, Stored procedures and advanced mapping, through the Spring framework to realize the management of JAVABean, dependency injection and transaction management, and finally realize the point redemption function.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced Network, Monitoring and Controls","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21307/ijanmc-2021-018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Abstract This paper describes the development process of the mobile point exchange system from demand analysis, outline design, detailed design and implementation. The system combines current business needs and uses collaborative filtering recommendation algorithms to solve the problem of how to calculate data similarity. The system is written in JAVA language, and uses a layered architecture model to separate business modules and functional modules. The front-end uses HTML, FreeMarker and Vue technologies to achieve page display and data rendering, and the persistence layer framework uses Mybatis to implement customized SQL, Stored procedures and advanced mapping, through the Spring framework to realize the management of JAVABean, dependency injection and transaction management, and finally realize the point redemption function.