implicit-feedback

There are 35 repositories under implicit-feedback topic.

  • etlundquist/rankfm

    Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data

    Language:Python170122536

  • gasevi/pyreclab

    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.

    Language:C++119152129

  • david-cortes/hpfrec

    Python implementation of 'Scalable Recommendation with Hierarchical Poisson Factorization'.

    Language:Python7951219

  • david-cortes/poismf

    (Python, R, C) Poisson matrix factorization (non-Bayesian version) (recommender systems)

    Language:C457213

  • jbochi/facts

    Matrix Factorization based recsys in Golang. Because facts are more important than ever

    Language:Go34414

  • enoche/ImRec

    A Pytorch Recommendation Framework with Implicit Feedback.

    Language:Python32363

  • usaito/unbiased-implicit-rec-real

    (WSDM2020) "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback"

    Language:Python30335

  • Jennytang1224/Need_a_Date

    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.

    Language:Python292210

  • david-cortes/recometrics

    (Python, R, C++) Library-agnostic evaluation framework for implicit-feedback recommender systems

    Language:C++26243

  • usaito/unbiased-implicit-rec

    (WSDM2020) "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback"

    Language:Python24213

  • hand10ryo/PyTorchCML

    PyTorchCML is a library of PyTorch implementations of matrix factorization (MF) and collaborative metric learning (CML), algorithms used in recommendation systems and data mining.

    Language:Python201132

  • usaito/unbiased-pairwise-rec

    (ICTIR2020) "Unbiased Pairwise Learning from Biased Implicit Feedback"

    Language:Python19215

  • LienM/recpack

    GitHub Mirror of RecPack: Experimentation Toolkit for Top-N Recommendation (see https://gitlab.com/recpack-maintainers/recpack)

    Language:Python17263

  • zealscott/SGDL

    Source code for Self-Guided Learning to Denoise for Robust Recommendation. SIGIR 2022.

    Language:Python16178

  • edervishaj/gan-mf-thesis

    This is the repository for the Master of Science thesis titled "GAN-based Matrix Factorization for Recommender Systems".

    Language:Python10203

  • lucashu1/CDN-RecSys

    A hybrid recommender system for suggesting CDN (content delivery network) providers to various websites

    Language:Jupyter Notebook8213

  • qxmd/ImplicitMF

    A set of matrix factorization techniques to provide recommendations for implicit feedback datasets.

    Language:Python8710

  • mlaprise/mfrec

    Recommender System toolkit

    Language:C7515

  • newlei/Set2setRank

    Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation, SIGIR 2021

    Language:Python5220

  • ddoeunn/Weighted-Regularized-Matrix-Factorization

    Recommender system weighted regularized matrix factorization in python

    Language:Python4115

  • gav-ctf/Solr-ctf-query-parser

    Reranks and expands Solr query returns using clickstream data

    Language:Java4100

  • dselivanov/bench-wrmf

    Benchmarking different implementations of weighted-ALS matrix factorization

    Language:R3402

  • StivenMetaj/Recommender_Systems_Challenge_2020

    Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi

    Language:Python3000

  • poludmik/NeuralCollaborativeFiltering.jl

    A Julia implementation of three different recommender systems based on the concept of Neural Collaborative Filtering.

    Language:Julia2100

  • stxupengyu/Matrix-Factorization-Implicit-Feedback

    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.

    2100

  • stxupengyu/NCF-for-Implicit-Feedback

    Neural collaborative filtering (NCF) method is used for Microsoft MIND news recommendation dataset.

    Language:Jupyter Notebook2102

  • AhmadRK94/RecSys-CF

    Implementation of various collaborative filtering methods for recommender systems with implicit feedback

    Language:Jupyter Notebook110

  • artdgn/ml-recsys-tools

    Tools for development of recommendation systems in Python.

    Language:Python110

  • MatteoFasulo/Netflix-Audience-Behaviour

    This project is a recommendation system built with implicit ALS algorithm using Netflix UK's watch history data. It provides personalized movie recommendations and exposes a FastAPI API route for easy integration.

    Language:HTML1201

  • somjit101/Netflix-Movie-Recommendation

    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.

    Language:Jupyter Notebook1100

  • zach96guan/Recommender_Demo

    Intern project to implement recommender demos for implicit feedback transaction data.

    Language:Jupyter Notebook1101

  • HwangHanJae/eCommerce-RecSystem

    ecommerce recommendation

    Language:Jupyter Notebook0100

  • jtonglet/Recommender-Systems-Polimi

    Competition for the Recommender Systems course @ PoliMi. The objective is to recommend relevant TV shows to users. Models were evaluated on their MAP@10.

    Language:Python0101

  • melaniasala/RecSys-Competition

    This project implements a robust recommender system for book recommendations, leveraging ensemble methods, user-specific strategies, XGBoost, and extensive data preprocessing to achieve high performance in the Recommender System 2023 Challenge hosted by Kaggle for students of Politecnico di Milano's Recommender Systems course.

    Language:Jupyter Notebook00

  • SimonCW/recommender-for-github-repos

    initial fork from

    Language:Jupyter Notebook10