Intelligent Shared Leasing Platform Based On Collaborative Filtering

With the continuous improvement of China’s modern economic and social development level and the continuous improvement of people’s living standards,the sharing economy has emerged in the current social environment and has achieved rapid development.At the same time,there have been major changes in the way people buy or exchange goods.With the continuous increase of idle resources,while bringing subversive changes to some industries,it also provides business opportunities for them,and the intelligent shared leasing model came into being.Therefore,it is necessary to build an intelligent shared leasing platform.The system mainly uses a series of technical means to effectively manage the products released by users,improve the utilization efficiency of material resources,standardize the product order process,and use collaborative filtering algorithms to effectively manage the products.Effective product recommendation for users to achieve collaborative creation of product value and resource integration and utilization.This paper firstly conducts a detailed study on the background,significance and domestic and foreign development of the subject,compares the modes of other leasing platforms,and analyzes the leasing mode in this subject.According to the software engineering life cycle,research and analyze the system,plan and establish the demand analysis of the system,carry out the overall planning of the general idea of the system design to complete the overall design,and then complete the detailed design,coding,debugging and testing through the overall design And so on a series of work.What this platform system uses is the MVC structure framework,the development mode of front-end and back-end separation.The system can dynamically manage data,effectively publish and maintain product information,and optimize collaborative filtering algorithms to improve the ability to recommend products to users.The system finally realizes the effective management of the front and the back,improves the management level of idle commodities,improves the utilization rate and recommendation efficiency of commodities,and realizes the purpose of scientific and unified management of commodity management.Its main content and system description are as follows:(1)This system introduces the research status of intelligent shared leasing and collaborative filtering algorithms at home and abroad,and introduces the framework,development technology and development environment required by this system.The front-end uses the Vue framework and combines Element UI and other personalized components for static page layout.The back-end uses Spring Boot framework,My SQL storage data and other technologies to write data and its interfaces.Python reproduces the collaborative filtering algorithm and improves it.(2)Innovate the collaborative filtering algorithm,combine the idea of matrix decomposition,and use the ALS least square method to decompose the user-item matrix and predict the score.The TF-IDF algorithm is used to extract item keywords as labels and establish user portraits.The data is divided into data sets and test sets for training.Finally,the keywords of the data are formed into a dictionary and the data sets are matched to find the corresponding item information.(3)Based on the overall planning of the system,the platform system is mainly divided into the following modules: user rights management,rental management,order logistics management,payment and recommendation modules.