Implementation-of-a-hadoop-based-movie-recommendation-system
通过编写代码,设计一个基于Hadoop的电影推荐系统,通过此推荐系统的编写,掌握在Hadoop平台上的文件操作,数据处理的技能。windows 10 hadoop 2.8.3 python 3.+ vscode MySQL 8.0
MGNN-SPred This is our Tensorflow implementation for the paper: WenWang,Wei Zhang, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, and Hongyuan Zha. 2020. Bey
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embeddi
This repo contains a tensorflow implementation of RecoGCN and the experiment dataset Running the RecoGCN model python train.py Example training outp
(中文文档|简体中文|English) 什么是推荐系统? 推荐系统是在互联网信息爆炸式增长的时代背景下,帮助用户高效获得感兴趣信息的关键; 推荐系统也是帮助产品最大限度吸引用户、留存用户、增加用户粘性、提高用户转化率的银弹。 有无数优秀的产品依靠用户可感知的推荐系统建立了良好的口碑,也有无数的公司依
This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).
GCE-GNN Code This is the source code for SIGIR 2020 Paper: Global Context Enhanced Graph Neural Networks for Session-based Recommendation. Requirement
A library of Recommender Systems This repository provides a summary of our research on Recommender Systems. It includes our code base on different rec
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
Movie Recommendation 🍿 System Watch Tutorial for this project Source IMDB Movie 5000 Dataset Inspired from this original repository. Features Simple
🔍 E-Commerce recommender demo 🔍 This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is str
recommendersystem Recommendation System to recommend top books from the dataset Introduction The recom.py is the main program code. The dataset is als
DGCN This is the official implementation of our WWW'21 paper: Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li, DGCN: Diversified Recommendation wi
DHCN Codes for AAAI 2021 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'. Please note that the default link
SGL This is our Tensorflow implementation for our SIGIR 2021 paper: Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian,and Xing
COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype
recommender Movies/TV Recommender. Recommends Movies, TV Shows, Actors, Directors, Writers. Setup Create file API_KEY and paste your TMDB API key in i
Implicit Fast Python Collaborative Filtering for Implicit Datasets. This project provides fast Python implementations of several different popular rec
Collaborative Variational Bandwidth Auto-encoder The codes are associated with the following paper: Collaborative Variational Bandwidth Auto-encoder f
Dependencies NOTE: This code has been updated, if you were using this repo earlier and experienced issues that was due to an outaded codebase. Please
SR-HGNN ICDM-2020 《Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks》 Environments python 3.8 pytorch-1.6 DGL 0.5.