Recommender System toolkit
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Updated
Aug 24, 2014 - C
Recommender System toolkit
Benchmarking different implementations of weighted-ALS matrix factorization
A recommender engine built for a Bay Area online dating website to maximize the successful matches by introducing hybrid recommender system and reverse match technique.
Matrix Factorization based recsys in Golang. Because facts are more important than ever
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Reranks and expands Solr query returns using clickstream data
A set of matrix factorization techniques to provide recommendations for implicit feedback datasets.
A hybrid recommender system for suggesting CDN (content delivery network) providers to various websites
Intern project to implement recommender demos for implicit feedback transaction data.
使用矩阵分解算法处理隐式反馈数据,并进行Top-N推荐。The matrix factorization algorithm is used to process the implicit feedback data and make top-N recommendation.
This is the repository for the Master of Science thesis titled "GAN-based Matrix Factorization for Recommender Systems".
Tools for development of recommendation systems in Python.
pyRecLab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, IA Lab and SocVis Lab.
Neural collaborative filtering (NCF) method is used for Microsoft MIND news recommendation dataset.
Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi
A case study of the Netflix Prize solution where, given anonymous data of users and the ratings given to movies, the objective to provide recommendations to users for movies which they would like, based on their past activity and taste.
Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation, SIGIR 2021
Recommender system weighted regularized matrix factorization in python
Source code for Self-Guided Learning to Denoise for Robust Recommendation. SIGIR 2022.
PyTorchCML is a library of PyTorch implementations of matrix factorization (MF) and collaborative metric learning (CML), algorithms used in recommendation systems and data mining.
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