Research And Implementation Of Fitness Club Management System Based On SSM

With the continuous innovation of science and technology and the continuous development of the contemporary Internet,people's fitness methods have become more diversified and more convenient.People on-line fitness clubs browse and search for fitness products to find relevant products that they are interested in,and achieve more convenient fitness services without leaving home.The system adopts O2 O mode to provide fitness enthusiasts and offline fitness clubs with an effective platform for connecting online and offline fitness services.Online: The system integrates offline services into online services for fitness enthusiasts to purchase fitness equipment and fitness classes online.Offline: Fitness members can use online purchase of fitness courses to offline physical gyms to participate in fitness classes taught by fitness instructors or other projects.For example,running,muscle exercises,etc.The client of the fitness club system is a browser,so it can be accessed without installation.Secondly,the server side of the system uses the SSM framework for web development,which has better scalability;in addition,the data is high in response to product browsing and retrieval.Read and write concurrently,using Redis technology to build a cache cluster,can quickly non-transactional access;Finally,after the user orders the system according to the user's previous purchase behavior,using the latent factor model and Pearson algorithm to the user did not buy fitness Predictive scoring of goods for users to recommend fitness products.The process of research and implementation of this system is as follows:1.Demand analysis phase: After establishing the final target of the system,the feasibility analysis of the system is performed from the factors of technology,economy,operation,etc.,and then the top-level use case analysis of the entire system is performed.The use case analysis is from the management.From the perspective of the members and the members of the gym,the non-functional requirements analysis was performed on the system.The analysis of the requirements was conducted fromthree aspects: security,scalability,and ease of use.2.Design stage: The overall and detailed design of the functional modules of the system is carried out.The overall and detailed design is divided into online and offline sections.The online section includes the display of home product categories,carousel display,and search display.,Products add features such as shopping carts and fitness products.The offline section includes maintenance activities such as fitness classes,fitness classes,fitness promotion columns,and fitness promotion products.3.Fitness product recommendation algorithm: Using user-based collaborative filtering,use the Pearson algorithm to calculate users similar to the users to be recommended,select the closest two similar users from among them,according to similar users' ratings of purchased fitness products,Calculate the score of the fitness product that the user is not recommended to purchase,and select the fitness product that the user has not purchased and has a high predicted score to perform the fitness product recommendation.Before using the Pearson algorithm to calculate similar users,we must use the latent factor model to fill the original sparse scoring matrix into a dense scoring matrix.In this paper,the time offset parameter is added to improve the latent factor model,which helps to improve the accuracy of restoring the missing scoring matrix.4.Implementation stage: Use Python,java,JavaScript language to encode the system,and implement each design module.5.Test phase: Use the black box test mode to test the system.Use a large number of test cases to ensure that the system can run safely and reliably.