基于安卓的购物推荐系统设计与实现

扬州大学本科毕业设计AbstractNowadays,with the rapid development of the Internet and e-commerce,electronicshopping has become the most important shopping method for modern people due to itsfast and convenient characteristics,and the products in the market have become more andmore abundant.However,the "information overload"caused by the rapid expansion ofproduct data makes it easy for consumers to get lost in a large amount of productinformation.Therefore,the birth of the recommendation system has brought great help toconsumers.According to user preferences,the personalized recommendation system usesbig data analysis to push the products that consumers have been paying attention to or maylike recently,and improve the user experience.This article designs and implements an Android-based shopping recommendationsystem.The focus is to develop an online shopping software that can recommend productsaccording to user preferences.The recommendation module uses a user-basedcollaborative filtering algorithm.The Java language is used to develop research anddevelopment on the Android Studio and Eclipse platforms.MySQL is selected for thedatabase.The data is communicated in real time through the HTTP network transmissionprotocol,and JSON packaging technology is used for data interaction.This paper first briefly describes the relevant background of the recommender systemand the current international development reality,and then gives a detailed introduction tothe relevant technologies used in the recommender system.In addition,it also analyzes theneeds and design of the recommender system in detail,and presents it in the last part.Theresults achieved by the recommendation system and important codes are summarized,andthe key tasks of this article are summarized.Keywords:Android system;Recommendation system;Collaborative filtering algorithm;E-commerce