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musicrecsys's Introduction

说明

本项目为《推荐系统开发实战》一书的演示案例,采用前后端分离实现,后端使用的是Python的Django框架,前端使用的是Vue,数据库为MySQL,禁止用做商业用户,如有需要联系我授权

注:《推荐系统开发实战》已经在各大电商上线,感兴趣的朋友可以进行关注!

实现思路

  • 利用网易云API获取部分数据
  • 基于标签进行歌单详情页的推荐、歌曲详情页的推荐、歌手详情页的推荐
  • 基于用户的协同过滤算法给用户推荐用户、个用户推荐歌曲
  • 基于物品的协同过滤算法给用户推荐歌手
  • 基于内容的推荐算法给用户推荐歌单
  • 个性化排行榜
  • 为你推荐(不同用户行为不同看到的为你推荐也不同)
  • 我的足迹,展示用户在站内的行为

后端依赖

  • Python版本为3.6
  • Python包和对应的版本在MusicRecSys/MusicRec/z-others/files/requirement.txt文件中
  • 安装依赖为 pip install -r requirement.txt

前端说明

  • 依赖Node.js,版本为10.13

运行说明

  • mysql新建musicrec数据库,将MusicRecSys/MusicRec/z-others/files/musicrec.sql 文件导入
  • 修改 MusicRecSys/MusicRec/MusicRec/settings.py 文件中的ALLOWED_HOSTS为本地IP地址和本地mysql配置信息
  • 修改 MusicRecSys/MusicRec-Vue/config/index.js 中的 serverUrl
  • 修改 MusicRecSys/MusicRec-Vue/src/assets/js/linkBase.js 中的 serverUrl
  • 进入 MusicRecSys/MusicRec 执行python manage.py runserver 0.0.0.0:8000
  • 进入 MusicRecSys/MusicRec-Vue 执行npm install / npm run dev
  • 浏览器输入 http://127.0.0.1:8001 访问

相关说明

  • 后台访问地址:http://127.0.0.1:8000/admin/ (admin,admin)
  • Navicat 破解版 (链接:https://pan.baidu.com/s/1dYtKQxnoSZywuRfgCOfPRQ 提取码:qw8k)
  • git lfs 上传管理大文件
    • 执行 git lfs install 开启lfs功能
    • 使用 git lfs track 命令进行大文件追踪 例如git lfs track "*.png" 追踪所有后缀为png的文件
    • 使用 git lfs track 查看现有的文件追踪模式
    • 提交代码需要将gitattributes文件提交至仓库. 它保存了文件的追踪记录
    • 提交后运行git lfs ls-files 可以显示当前跟踪的文件列表
    • 将代码 push 到远程仓库后(git lfs push),LFS 跟踪的文件会以『Git LFS』的形式显示:
    • clone 时 使用'git clone' 或 git lfs clone均可

About Me

ID:Thinkgamer

Email:[email protected]

微信:


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注明:禁止用作商业用途

musicrecsys's People

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