在线音乐智能推荐系统设计与实现

摘要现在，网络逐渐成为人们日常生活的必需品。网络基础建设的改善让许多用户可以自由地查找、下载和收听音乐。人们生活中放松娱乐也渐渐地离不开听音乐。随着在线音乐的兴起，各大音乐平台越来越多。面对海量的冗杂信息，人们收听音乐的时，经常因为歌曲信息繁多，找不到自己喜欢的音乐。为了解决这个问题，音乐领域引入了推荐。使用推荐算法，可以给用户提供音乐推荐，准确的音乐推荐会让用户在获取喜欢的音乐的过程中得到良好的用户体验，降低用户时间成本。本文主要基于协同过滤设计并实现了在线音乐智能推荐系统。系统前端的用户交互界面使用ue.js开发，后端的设计与开发使用JAVA中的SSM框架。数据库用了MySQL。该在线音乐网站提供了用户登录注册，完整的音乐播放器功能，后台管理功能等等。通过隐式的收集在线音乐网站用户日常使用的各种行为信息，然后分析用户操作信息得到给用户的音乐推荐是系统的重点。对用户在系统上产生的种种操作信息的收集，从用户的操作得到用户对歌曲的喜爱程度。然后通过基于物品和基于用户的协同过滤算法得到用户的音乐列表推荐，给用户推荐用户可能喜欢的音乐。关键词：音乐推荐系统，协同过滤，推荐算法AbstractNowadays,the Internet is gradually becoming a necessity in people's daily lives.Theimprovement of internet infrastructure has allowed many users to find,download and listen tomusic freely.People are gradually becoming more and more inseparable from listening tomusic for relaxation and entertainment in their lives.With the rise of online music,there aremore and more major music platforms.Faced with the huge amount of information,peopleoften cannot find their favorite music when listening to music because of the large amount ofinformation about songs.In order to solve this problem,recommendation systems have beenintroduced in the music field.By using recommendation algorithms,music recommendationscan be provided to users.Accurate music recommendations will give users a good userexperience in getting their favorite music and reduce their time cost.In this paper,we design and implement an online music recommendation system basedon collaborative filtering.The front-end user interaction interface is developed using Vue.js,and the back-end design and development uses the SSM framework in JAVA.The onlinemusic website provides user login and registration,complete music player function,backendmanagement function and so on.By implicitly collecting various behavioral informationabout the daily use of the online music website users,and then analyzing the user behavior toget the music recommendation to the users is the focus of the system.The collection ofvarious behavioral information generated by users on the website,the user's favorite songs areobtained by collecting,commenting,playing and other behaviors.Then the user's music listrecommendation is obtained using the user-based collaborative filtering and item-basedcollaborative filtering algorithms to recommend to the user the music that the user may like.Key words:music recommendation system,collaborative filtering,recommendationalgorithm.目录摘要..2Abstract.….31绪论…1.1研究背景及意义1.1.1研究背景.1.1.2研究意义21.2国内外研究现状.31.3论文框架结构….52相关理论与技术….62.1协同过滤算法..62.1.1基于用户的协同过滤.62.1.2基于物品的协同过滤2.1.3相似度的计算...72.2系统开发框架.92.2.1ue框架92.2.2SSM框架.93音乐推荐系统的分析…113.1可行性分析…113.2业务需求分析113.2.1用户管理功能113.2.2音乐管理功能.123.2.3音乐推荐功能.123.2.4后台管理模块.133.2.5非功能性需求分析.133.3系统分析….134音乐推荐系统的设计194.1整体架构设计..194.2功能模块设计20