Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data
machine-learning collaborative-filtering learning-to-rank recommender-system factorization-machines recommendation implicit-feedback
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implicit-feedback
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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.
rating svd knn implicit-feedback rating-prediction recommendation-algorithm alternating-least-squares
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Python implementation of 'Scalable Recommendation with Hierarchical Poisson Factorization'.
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(Python, R, C) Poisson matrix factorization (non-Bayesian version) (recommender systems)
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A Pytorch Recommendation Framework with Implicit Feedback.
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Matrix Factorization based recsys in Golang. Because facts are more important than ever
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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.
cold-start prediction-model implicit-feedback hybrid-recommendation dating-website profile-similarity weighted-similarity-score
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(Python, R, C++) Library-agnostic evaluation framework for implicit-feedback recommender systems
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(WSDM2020) "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback"
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(WSDM2020) "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback"
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GitHub Mirror of RecPack: Experimentation Toolkit for Top-N Recommendation (see https://gitlab.com/recpack-maintainers/recpack)
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PyTorchCML is a library of PyTorch implementations of matrix factorization (MF) and collaborative metric learning (CML), algorithms used in recommendation systems and data mining.
python machine-learning pytorch collaborative-filtering metric-learning recommender-system implicit-feedback
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(ICTIR2020) "Unbiased Pairwise Learning from Biased Implicit Feedback"
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Source code for Self-Guided Learning to Denoise for Robust Recommendation. SIGIR 2022.
deep-learning pytorch recommender-system implicit-feedback denoising graph-neural-networks robust-learning sigir2022
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This is the repository for the Master of Science thesis titled "GAN-based Matrix Factorization for Recommender Systems".
collaborative-filtering matrix-factorization generative-adversarial-network gan recsys ebgan recommender-systems autoencoders feature-matching implicit-feedback top-n-recommendations
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A set of matrix factorization techniques to provide recommendations for implicit feedback datasets.
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A hybrid recommender system for suggesting CDN (content delivery network) providers to various websites
cdn collaborative-filtering recommendation-system recommender-system implicit-feedback lightfm hybrid-recommender-system
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Recommender System toolkit
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Recommender system weighted regularized matrix factorization in python
wmf collaborative-filtering matrix-factorization recommender-system implicit-feedback paper-code wrmf one-class-collaborative-filtering
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🚀 Production-ready hybrid recommender system for e-commerce. Combines collaborative filtering & content-based ML with FastAPI backend, React
machine-learning ecommerce collaborative-filtering matrix-factorization recommendation-engine tf-idf recommender-system implicit-feedback hybrid-recommender-system content-based-filtering mlops fastapi ranking-metrics
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