Project Title: Recommender System with Social Network Analysis

Description

This project is a collaborative effort by three students from FEUP for the curricular unit CAC (Machine Learning Complements). The project focuses on developing a recommender system integrated with social network analysis techniques.

Team Members

• Henrique Silva
• João Pinheiro
• João Oliveira
• Ricardo Cavalheiro

Project Overview

The goal of this project is to design and implement a recommender system that leverages social network data to provide personalized recommendations. The system will analyze the relationships between users within a social network and use this information to enhance the recommendation process.

Key Features

• Integration of social network data
• Collaborative filtering algorithms
• User-item interaction analysis
• Personalized recommendations
• Evaluation metrics implementation

Technologies Used

• Python
• NetworkX
• Pandas
• NumPy
• Scikit-learn
• Flask (for web application, if applicable)
• HTML/CSS/JavaScript (for web application, if applicable)

Installation

1. Clone the repository:

   git clone https://github.com/jogp10/recommender-system.git

2. Install the required dependencies:

    pip install -r requirements.txt

LICENSE

This project is licensed under the MIT License.