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RecommendSystem\n\n[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)\n\n\u003e [!WARNING]\n\u003e\n\u003e 本项目仅供学习参考，未经生产环境测试\n\n## 项目简介\n\n本项目为推荐系统与数据仓库课程的结课设计，一个基于 Django 的药物推荐系统，旨在通过现代推荐算法与数据可视化技术，帮助用户快速获得相关药品推荐。它展示了推荐系统的核心功能和实现方法，适合作为学习和研究推荐系统的入门项目。\n\n## 数据集\n\n* 原始数据集来源于[Kaggle](https://www.kaggle.com/)，数据集链接如下：\n\n* [Medicine_Recommendation](https://www.kaggle.com/datasets/saratchendra/medicine-recommendation/data)\n\n* 此数据集遵循 [CC0: Public Domain](https://creativecommons.org/publicdomain/zero/1.0/) 协议。根据该协议，您可以自由使用、修改和分发该数据集，而无需署名。\n\n* 本项目数据集经过数据预处理以及数据清洗，具体修改内容如下：\n  * 替换 'Company_Name' 中 Rating 为 ‘Ratings’ 中 Short-form 对应 Rating；\n  * 合并 ‘Medicine_description’ 与 ‘Company_Name’ ；\n  * 去除无关列 ‘S.No’, ‘NSE_Symbol’, ‘Industry’ ；\n  * 填充缺失的 ‘description’ 值为 ‘Unkown’。\n\n## 实现特性\n\n* **用户管理：**\n  * **登陆系统：** 基于 Django 的用户认证系统。\n  * **权限控制：** 未登录用户无法访问。\n* **推荐系统：** \n  * **支持四种推荐算法：**\n    * 基于协同过滤的推荐\n    * 基于内容的推荐\n    * 基于标签的推荐\n    * 基于隐语义的推荐\n* **数据可视化：**\n  * **支持三种数据可视化：**\n    * 不同疾病对应药品数量\n    * 药品评分分布\n    * 药品数量排名前10的公司\n* **界面优化：** \n  * **页面美化：** 基于[Bootstrap](https://getbootstrap.com/), [jQuery](https://jquery.com/)对页面进行美化。\n  * **异步加载：** AJAX 实现异步加载内容。\n  * **速度优化：** JS及CSS文件保存在本地，加快加载速度，避免无网络演示时无法使用。\n  * **友好的用户提醒：** 当用户使用系统时，会适时弹出提示/播放动画效果。\n\n## 技术栈\n\n* **后端：** Django\n* **数据库：** MySQL\n* **前端：** HTML, [Bootstrap](https://getbootstrap.com/), [jQuery](https://jquery.com/)\n* **数据处理**：pandas, numpy\n* **推荐系统实现**：scikit-learn\n\n## 环境要求\n\n- [Python](https://www.python.org/)\n- [MySQL](https://www.mysql.com/)\n- 现代浏览器（本人仅测试在Safari和Chrome中未发现明显错误）\n\n## 快速开始\n\n1. 克隆仓库\n\n   ```bash\n   git clone https://github.com/hevenkin/RecommendSystem.git\n   cd RecommendSystem\n   ```\n\n2. 创建数据库\n\n   ```bash\n   mysql -u \u003cUSER_NAME\u003e -p\n   ```\n\n   ```mysql\n   CREATE DATABASE \u003cDATABASE_NAME\u003e;\n   ```\n\n3. 配置数据库连接\n\n   按下列代码中注释修改 recommendation_project 中的 settings.py 以连接数据库：\n\n   ```python\n   DATABASES = {\n       \"default\": {\n           #\"ENGINE\": \"django.db.backends.sqlite3\",\n           #\"NAME\": BASE_DIR / \"db.sqlite3\",\n           \"ENGINE\": \"django.db.backends.mysql\",\n           \"NAME\": \"\u003cDATABASE_NAME\u003e\", # 在此处输入上一步你创建的数据库名\n           \"USER\": \"\u003cUSER_NAME\u003e\", # 在此处输入你的数据库用户名\n           \"PASSWORD\": \"\u003cUSER_PASSWORD\u003e\", # 在此处输入你的数据库密码 \n           \"HOST\": \"\u003cHOST\u003e\", # 在此处输入你的数据库地址（一般为localhost）\n           \"PORT\": \"\u003cPORT\u003e\", # 在此处输入你的数据库端口（一般为3306）\n       }\n   }\n   ```\n\n4. 初始化数据库\n\n   在终端中运行以下命令初始化数据库和数据：\n\n   ```bash\n   python manage.py makemigrations\n   python manage.py migrate\n   python manage.py import_drugs\n   ```\n\n5. 启动服务器：\n\n   ```bash\n   python manage.py runserver\n   ```\n\n6. 打开浏览器访问http://127.0.0.1:8000\n\n7. You're done! Enjoy!\n\n## 贡献\n\n欢迎任何形式的贡献！请随意提交 Issue 或 Pull Request。\n\n## 许可证\n\n本项目使用 Apache License 2.0 许可证，详情请查看 [LICENSE](LICENSE) 文件。\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhevenkin%2Frecommendsystem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhevenkin%2Frecommendsystem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhevenkin%2Frecommendsystem/lists"}