This project is a Proof of Concept (POC) for a Movie Recommendation System. The goal of this system is to provide personalized recommendations to users based on their preferences and behavior using The Movies Dataset.
- User Profiling: Collects and analyzes user data to create detailed user profiles.
- Content-Based Filtering: Recommends items similar to those the user has shown interest in.
- Collaborative Filtering: Suggests items based on the preferences of similar users.
- Hybrid Approach: Combines content-based and collaborative filtering for more accurate recommendations.
- Real-Time Recommendations: Provides up-to-date suggestions as user data changes.
- Java: The core programming language used for developing the recommendation algorithms.
- Apache Mahout: Mahout is a scalable ML-focused library perfect for Collaborative Filtering-based recommendation systems.
- Clone the repository:
git clone https://github.com/xmacedo/MovieRecommendationSystem.git- Navigate to the project directory:
cd MovieRecommendationSystem- Install the required dependencies:
- Olhar algoritmo Knn (K vizinhos), similiradide de cosseno,