IEEE

Collaborative Filtering Item Recommendation Methods based on Matrix Factorization and Clustering Approaches

Abstract: This paper studies various collaborative filtering item recommendation methods based on matrix factorization and clustering approaches. We develop six methods that are modified based on ...
IEEE

An Efficient Non-Negative Matrix-Factorization-Based Approach to Collaborative Filtering for Recommender Systems

Abstract: Matrix-factorization (MF)-based approaches prove to be highly accurate and scalable in addressing collaborative filtering (CF) problems. During the MF process, the non-negativity, which ...
GitHub

A comprehensive restaurant recommendation system that combines multiple recommendation approaches including content-based filtering, collaborative filtering, matrix ...

restaurant_recommendation_system/ ├── src/ │ ├── data/ │ │ ├── generate_data.py # Data generation utilities │ │ └── data_loader.py # Data loading and preprocessing │ ├── models/ │ │ ├── ...
GitHub

jayateja-a/Movie_recommendation_analysis_using_data_analytics

Open your browser and navigate to http://127.0.0.1:5000/. Note: On first run, the model will be trained (takes 5-10 minutes). Subsequent runs will load the saved ...