RecSysCOEN6313

Recommendation system

Build setup

# install front-end
cd frontend
npm install

# serve with hot reload at localhost:8080
npm run dev

# build for production/Flask with minification
# Creates the dist folder in the root of application.
# The production flask application use this folder
npm run build


# install back-end
cd ../backend
virtualenv -p python3 env
source env/bin/activate
pip install -r requirements.txt
cd ..

# serve back-end at localhost:5000
FLASK_APP=run.py flask run
# or
python3 run.py

Data Source Introduction

https://tianchi.aliyun.com/datalab/dataSet.html?spm=5176.100073.0.0.583d3ea7v2AdZk&dataId=649

Data link on Google Drive

https://drive.google.com/open?id=1oWW5DNOCmgqooILF6CavPxPTdJVY-J_c https://drive.google.com/open?id=1wpcxDkKKUE-e56kucRwxGZQXEyHuYkFA

Learning Tree-based Deep Model for Recommender Systems

https://arxiv.org/pdf/1801.02294.pdf

Real-Time Personalized Recommendation System - Alibaba Cloud Community

https://www.alibabacloud.com/blog/real-time-personalized-recommendation-system_115904

推荐系统主要算法总结及Youtube深度学习推荐算法实例概括

https://www.jiqizhixin.com/articles/2017-07-09-5

一文综述用于推荐系统的所有深度学习方法 - CSDN博客

https://blog.csdn.net/kingzone_2008/article/details/80692113