This is our implementation of ENMF: Efficient Neural Matrix Factorization (TOIS. 38, 2020). This also provides a fair evaluation of existing state-of-the-art recommendation models.
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Updated
Jul 22, 2021 - Python
This is our implementation of ENMF: Efficient Neural Matrix Factorization (TOIS. 38, 2020). This also provides a fair evaluation of existing state-of-the-art recommendation models.
The code repository for the paper: Peijie et al., Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering. IEEE TKDE, 2023.
Source code for the RecSys 2024 paper "Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation."
A movie recommendation system utilizing a Graph Neural Network (GNN) framework implemented in Jupyter Notebook
Deep learning music matcher that connects users based on complex listening patterns using GNN embeddings and Last.fm data.
An institutional Deal Flow OS connecting founders and investors. Built on a Next.js/FastAPI microservices architecture, it features a PyTorch LightGCN/SBERT recommendation engine, a Zero-Knowledge E2EE Vault for secure data, and Groq-powered GenAI for automated due diligence.
RecSys Codes based on PyTorch
🧴 妆策AI 面向美妆新零售实战场景的智能推荐与营销转化平台 | AI-powered Beauty New Retail Platform | 15+ Algorithms | GBDT AUC=0.9993 | LightGCN HR@10=0.8413 | Six-Dimension Scoring
Comparative study of graph-based recommendation models NGCF and LightGCN, reproducing benchmark results on Amazon-book and evaluating generalization on Amazon-software-2023 using Recall@20 and NDCG@20.
PyTorch implementation of LightGCN (He et al., SIGIR 2020) trained on Gowalla - achieves 97.3% of paper's Recall@20 in 400 epochs.
A Recommender System for Google Maps reviews using LightGCN.
Heterogeneous graph neural network music recommender with Playlist-Track-Artist relations. Extends Stanford CS224W article with 5 GNN architectures.
Implementation of various collaborative filtering methods for recommender systems with implicit feedback
Personalized movie recommendation platform built with LightGCN, PyTorch, and Streamlit.
GNN-based recommendation under extreme data sparsity for WuxiaWorld web serials
Comparative Analysis of Recommender Systems on Goodreads Data: A study benchmarking SVD, SVAE, NGCF, and LightGCN models to understand their efficacy in book recommendation.
GNN-based movie recommendation system using LightGCN on MovieLens 100K, with anomaly detection
Two-Tower RecSys + FAISS retrieval + cold-start demo (Amazon Video Games 2023)
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