implicit-feedback | Topic | Ecosyste.ms: Repos

Topic: "implicit-feedback"

etlundquist/rankfm

Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data

Language: Python - Size: 2.15 MB - Last synced at: 2 days ago - Pushed at: 10 months ago - Stars: 176 - Forks: 37

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++ - Size: 1.8 MB - Last synced at: 10 days ago - Pushed at: almost 5 years ago - Stars: 122 - Forks: 28

david-cortes/hpfrec

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

Language: Python - Size: 315 KB - Last synced at: 16 days ago - Pushed at: about 1 month ago - Stars: 79 - Forks: 20

david-cortes/poismf

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

Language: C - Size: 552 KB - Last synced at: 7 days ago - Pushed at: about 1 month ago - Stars: 46 - Forks: 13

jbochi/facts

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

Language: Go - Size: 10.7 KB - Last synced at: about 2 months ago - Pushed at: over 7 years ago - Stars: 33 - Forks: 4

david-cortes/recometrics

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

Language: C++ - Size: 221 KB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 28 - Forks: 3

enoche/ImRec

A Pytorch Recommendation Framework with Implicit Feedback.

Language: Python - Size: 4.61 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 28 - Forks: 3

usaito/unbiased-implicit-rec-real

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

Language: Python - Size: 478 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 28 - Forks: 5

usaito/unbiased-implicit-rec

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

Language: Python - Size: 395 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 20 - Forks: 3

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: Python - Size: 418 KB - Last synced at: 6 days ago - Pushed at: almost 3 years ago - Stars: 20 - Forks: 3

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: Python - Size: 1.79 MB - Last synced at: over 2 years ago - Pushed at: over 7 years ago - Stars: 20 - Forks: 7

usaito/unbiased-pairwise-rec

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

Language: Python - Size: 28.3 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 5

zealscott/SGDL

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

Language: Python - Size: 866 KB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 15 - Forks: 8

LienM/recpack

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

Language: Python - Size: 6.48 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 13 - Forks: 3

edervishaj/gan-mf-thesis

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

Language: Python - Size: 85 MB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 9 - Forks: 4

lucashu1/CDN-RecSys

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

Language: Jupyter Notebook - Size: 5.14 MB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 8 - Forks: 3

mlaprise/mfrec

Recommender System toolkit

Language: C - Size: 711 KB - Last synced at: about 2 years ago - Pushed at: almost 11 years ago - Stars: 6 - Forks: 5

newlei/Set2setRank

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

Language: Python - Size: 98.6 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 0

dselivanov/bench-wrmf

Benchmarking different implementations of weighted-ALS matrix factorization

Language: R - Size: 87.9 KB - Last synced at: 7 days ago - Pushed at: almost 8 years ago - Stars: 3 - Forks: 2

poludmik/NeuralCollaborativeFiltering.jl

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

Language: Julia - Size: 46.3 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

StivenMetaj/Recommender_Systems_Challenge_2020 Fork of SamueleMeta/recommender-systems

Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi

Language: Python - Size: 7.43 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 0

stxupengyu/NCF-for-Implicit-Feedback

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

Language: Jupyter Notebook - Size: 53.7 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 2

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.

Size: 206 KB - Last synced at: over 2 years ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 0

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: HTML - Size: 32.5 MB - Last synced at: 4 days ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 1

AhmadRK94/RecSys-CF

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

Language: Jupyter Notebook - Size: 8.33 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

ddoeunn/Weighted-Regularized-Matrix-Factorization

Recommender system weighted regularized matrix factorization in python

Language: Python - Size: 63.5 KB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 5

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 Notebook - Size: 9.07 MB - Last synced at: 3 months ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

artdgn/ml-recsys-tools Fork of DomainGroupOSS/ml-recsys-tools

Tools for development of recommendation systems in Python.

Language: Python - Size: 2.39 MB - Last synced at: 5 days ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0

zach96guan/Recommender_Demo

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

Language: Jupyter Notebook - Size: 87.5 MB - Last synced at: almost 2 years ago - Pushed at: almost 6 years ago - Stars: 1 - Forks: 1

AndryVon/hpf

A high precision floating-point arithmetic module.

Language: Python - Size: 38.1 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

asenacak/recommenderSystems-SteamVideoGames

Language: Jupyter Notebook - Size: 1.65 MB - Last synced at: about 2 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

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: Python - Size: 16.7 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 1

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 Notebook - Size: 166 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0