A unified, comprehensive and efficient recommendation library
-
Updated
Feb 24, 2025 - Python
A unified, comprehensive and efficient recommendation library
Repository hosting code for "Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152).
This is a repository of public data sources for Recommender Systems (RS).
🛍 A real-world e-commerce dataset for session-based recommender systems research.
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
CORE is a plug-and-play conversational agent for any recommender system.
The code for the paper "MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation" (ACM MM'23).
The code for the paper "RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction" (WWW 24 short paper)
A self-assessment tool by @NC3-LU to help business owners implement a better cybersecurity strategy.
Dartmouth Course Reviews, Rankings, and Recommendations
Simple CLI Tool For Generating Available Telegram Usernames
🎥 Simple Python implementation of Funk SVD for MovieLens movie collaborative recommendations.
Amazon Personalize Langchain extensions to support invoking and retrieving personalized recommendations from your Amazon Personalize resources
[KDD 2025] The source code for UQABench
Market basket recommendations using association rules and apriori
Recommendation for Amazon movie review data
automate the boring stuff!
Codebase for paper: "Improving GCN with Transformer layer in social-based items recommendation"
Add a description, image, and links to the recommendations topic page so that developers can more easily learn about it.
To associate your repository with the recommendations topic, visit your repo's landing page and select "manage topics."