Movie-Recommender-System is a web application using which a user can select his/her watched movie from list and system will recommend 5 movies to watch according to user interest. For more information about project : Email: [email protected] Python | Streamlit Link: https://movie-recommender-prooject.herokuapp.com/
DGTN: Dual-channel Graph Transition Network for Session-based Recommendation This repository contains PyTorch Implementation of ICDMW 2020 (NeuRec @ I
TorchRec (Experimental Release) TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale
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
Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filte
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
SEFrame This repository contains the code for the paper "An Efficient and Effective Framework for Session-based Social Recommendation". Requirements P
A library of Recommender Systems This repository provides a summary of our research on Recommender Systems. It includes our code base on different rec
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
FairGNN A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (
A general purpose recommender metrics library for fair evaluation.
Basic Information: This code is released for the papers: Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang and Meng Wang. A Neural Influence Dif
Detecting Beneficial Feature Interactions for Recommender Systems (L0-SIGN) This is our implementation for the paper: Su, Y., Zhang, R., Erfani, S., &
DHCN Codes for AAAI 2021 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'. Please note that the default link
LESSR A PyTorch implementation of LESSR (Lossless Edge-order preserving aggregation and Shortcut graph attention for Session-based Recommendation) fro
This project will access your last listened songs on Spotify using its API, then it will request the user to select 5 favorite songs in that list, on which the API will proceed to make 50 recommendat
Books-Recommendation Business Problem During the last few decades, with the rise
plex-recommender Description: Get movie/tv recommendations based on your current
Recommendation engines are one of the most well known, widely used and highest value use cases for applying machine learning. Despite this, while there are many resources available for the basics of
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
recmetrics A python library of evalulation metrics and diagnostic tools for recommender systems. **This library is activly maintained. My goal is to c
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