MATLAB-Based Recommendation System Source Code

This article presents a comprehensive MATLAB implementation of a recommendation system utilizing collaborative filtering algorithms. The collaborative filtering approach, a widely-adopted recommendation technique, leverages historical user behavior and preference data to predict items or services that users might find interesting. This MATLAB source code provides a functional implementation featuring key components such as user-item matrix processing, similarity calculation functions (using cosine similarity or Pearson correlation), and prediction algorithms for generating recommendations. The system demonstrates practical applications across various domains including e-commerce platforms, video streaming services, and music applications, enabling personalized user experiences through data-driven recommendations. For developers and researchers interested in MATLAB programming and recommendation algorithms, this source code serves as an excellent educational resource, featuring clear code structure with comments explaining the algorithm workflow, matrix operations for efficient computation, and customizable parameters for different application scenarios.