hybrid-recommender-system

Here are 31 public repositories matching this topic...

MaurizioFD / RecSys2019_DeepLearning_Evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Updated May 25, 2023
Python

sukeshsangam / Deep-Learning-Model-for-Hybrid-Recommendation-Engine

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A Hybrid recommendation engine built on deep learning architecture, which has the potential to combine content-based and collaborative filtering recommendation mechanisms using a deep learning supervisor

data-science machine-learning recommendation-system recommendation-engine hybrid-recommender-system hybrid-recommendation-engine

Updated Jun 25, 2018
Python

YuzhouPeng / Linedin-User-profile-Hybrid-Recommendation

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Hybrid recommedation for talents

word2vec collaborative-filtering recommender-system doc2vec content-based-recommendation hybrid-recommender-system

Updated Apr 4, 2019
Python

faizanahemad / Hybrid-Weighted-Embedding-Recommender

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A Hybrid Recommendation system which uses Content embeddings and augments them with collaborative features. Weighted Combination of embeddings enables solving cold start with fast training and serving

deep-learning tensorflow embeddings recommendation-system recommender-system hybrid-recommender-system

Updated Dec 8, 2022
Python

Divyanshu169 / IT556_Worthless_without_coffee_DA-IICT_Final_Project

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This is a book recommendation engine built using a hybrid model of Collaborative filtering, Content Based Filtering and Popularity Matrix.

collaborative-filtering recommender-system content-based-recommendation hybrid-recommender-system goodbooks-10k popularity-recommender

Updated Nov 25, 2020
Python

SamueleMeta / recommender-systems

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Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi

slim matrix-factorization recommender-system bayesian-optimization polimi elasticnet user-collaborative-filtering item-collaborative-filtering content-based-recommendation alternating-least-squares hybrid-recommender-system implicit-feedbacks rp3beta

Updated Mar 15, 2021
Python

MaurizioFD / CFeCBF

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This repository contains the core model we called "Collaborative filtering enhanced Content-based Filtering" published in our UMUAI article "Movie Genome: Alleviating New Item Cold Start in Movie Recommendation"

multimedia collaborative-filtering recsys recommender-system content-based-recommendation hybrid-recommendation hybrid-recommender-system feature-weighting hybrid-recommender

Updated Apr 3, 2019
Python

mesudepolat / Hybrid-Recommender-System

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Combines user-based and item-based recommendation systems to deliver personalized movie suggestions, utilizing user preferences and film characteristics.

recommendation-system hybrid-recommender-system user-based-recommendation item-based-recommendation

Updated Apr 1, 2024
Python

amanjeetsahu / Recommender-Systems-Using-Python

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This repo contains my practice and template code for all kinds of recommender systems using SupriseLib. More complex and hybrid Recommender Systems can build on top of these template codes.

python evaluation python3 collaborative-filtering recommender-system jupyter-notebooks content-based-recommendation surprise-python hybrid-recommender-system scikit-surprise surprise-library

Updated Jul 24, 2020
Python

dzvlfi / Recommendation-System-Algorithms

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Recommendation System Algorithm

python recommendation-system ab-testing apriori-algorithm content-based-recommendation hybrid-recommender-system collaborative-filter

Updated Sep 20, 2019
Python

Gaurav-Pande / Recommendation_systems

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Auto encoders based recommendation system

ratings deep-learning neural-network embeddings collaborative-filtering recommender-system weights autoencoders movie-recommendation auto-encoders hybrid-recommender-system product-recommendations collaborating-filtering

Updated Aug 8, 2020
Python

lpraat / RecSys

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Set of recommender systems

slim bpr recommender-system polimi hybrid-recommender-system bprslim

Updated Apr 16, 2019
Python

Lodz97 / RecSys-PoliMi-2020

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The objective of the competition was to create the best recommender system for a book recommendation service by providing 10 recommended books to each user. The evaluation metric was MAP@10.