USC DSCI 553 - Foundations & Applications of Data Mining - Spring 2024 - Prof. Wei-Min Shen

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

This study aims to investigate the effectiveness of three Transformers (BERT, RoBERTa, XLNet) in handling data sparsity and cold start problems in the recommender system. We present a Transformer-based hybrid recommender system that predicts missing ratings and ex- tracts semantic embeddings from user reviews to mitigate the issues.

BoardGameGeek Recommender System is a start-to-finish project, from sourcing the data to a hybrid recommender system utilizing both content-based and collaborative filtering.

Content-based Filtering, Neighborhood-based Collaborative Filtering

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

The "Music Recommender System using Spotify API" project aims to create a personalized music recommendation system for users based on their listening preferences and behavior. By leveraging the Spotify API, we can access a vast collection of music data, including tracks, artists, genres, and user playlists.

A movie recommender application

This is an app for collaborative and hybrid filtering using multiple csv data a model is trained and a flask is used for the web representation of model

A hybrid group recommendation system for film and TV content using Letterboxd profile data

Using hybrid recommender system with apriori algorithm, content-based and collaborative filtering method for predicting users interactions and then recommend them for users.

2021년 경상북도 데이터 경진대회 | 추천 알고리즘을 이용한 맞춤형 식품 추천 서비스

Hybrid recommendation system using LightFM library and different loss functions on retail data.

Explore the Recommendation System Interview Prep Guide! This GitHub repository provides curated interview questions and answers for Data Scientists. Elevate your knowledge of recommendation systems, navigate technical interviews with confidence, and succeed in the dynamic field of data science focused on recommendation system applications.

Explore the Hybrid Recommender System on E-commerce Data repository! This GitHub project showcases a solution for building a hybrid recommender system. Dive into the code, discover innovative approaches, and enhance your understanding of creating effective recommendation systems tailored for E-commerce Data.

Amar deep architectures for hybrid recommenders with GNNs

The goal of this project is to implement a Hybrid Recommender System that combines item-based and user-based recommendation methods to provide movie recommendations for a specific user. The system aims to offer a total of 10 movie recommendations by using both methods.

Hybrid Recommender System for Computer Science Papers | Master's Thesis Project 2023

This repository contains a recommendation model for content-based, collaborative filtering and hybrid model approaches. It also exhibits popularity model for new-users to address cold-start problem. It evaluates the model using metrics like coverage, diversity and novelty

This repository houses the codebase for a Book Recommendation System, crafted using collaborative filtering, Flask, and cosine similarity. The system employs advanced machine learning techniques to generate personalized book recommendations based on user preferences.