Finding the perfect Xfinity plan shouldn't be complicated! Xfinity SmartMatch is an intelligent recommendation system that understands user needs through natural language processing (NLP) and AI-driven analysis. Our hybrid model uses content-based filtering and simulated collaborative filtering to suggest the most cost-effective and optimized plans for users.
Experience the future of personalized recommendations—fast, smart, and cost-efficient!
Xfinity SmartMatch is an AI-powered recommendation engine designed to help users select the most suitable Xfinity products based on their personal preferences and usage patterns.
- Natural Language Understanding: Users can describe their needs in plain English (e.g., "I need fast internet for gaming and a mobile plan under $50").
- AI-Driven Filtering: Our model analyzes plan details and optimizes recommendations using a hybrid approach combining content-based filtering (plan details) and collaborative filtering (simulated user preferences).
- Cost Optimization Engine: Finds the most affordable options while maintaining high service quality.
- Personalized Insights: Users receive AI-powered plan comparisons with real-time savings estimates.
- Seamless User Experience: A sleek, interactive interface allows easy selection and fine-tuning of recommendations.
Unlike generic comparison tools, Xfinity SmartMatch doesn't just list plans—it understands user intent and behavior, ensuring the most tailored and budget-friendly choices.
- Programming Language: Python
- Framework: Streamlit (for UI and interaction)
- Database: SQLite3 (for storing plan data and user preferences)
- AI Model: Gemini AI Labs (for NLP and recommendation logic)
- Version Control: GitHub
Xfinity-SmartMatch/
│-- app.py # Streamlit frontend
│-- recommender.py # AI-based recommendation logic
│-- database.py # SQLite3 database setup and queries
│-- requirements.txt # Dependencies
│-- README.md # Project documentation
│-- assets/ # Logo and design assets
│-- data/ # Sample datasets (Xfinity plans)
│-- .github/ # GitHub workflows (optional CI/CD)
- Python 3.8+
- pip
-
Clone the repository:
git clone https://github.com/yourusername/Xfinity-SmartMatch.git cd Xfinity-SmartMatch -
Install dependencies:
pip install -r requirements.txt
-
Set up the database:
python database.py
-
Run the application:
streamlit run app.py
- Access the application through your web browser at
http://localhost:8501(default Streamlit port) - Enter your preferences using natural language
- Review the personalized recommendations
- Fine-tune your preferences if needed
- Select your preferred plan
Our recommendation system uses a hybrid approach:
- Content-Based Filtering: Analyzes Xfinity plan features and matches them to user requirements
- Simulated Collaborative Filtering: Predicts user satisfaction based on similar usage patterns
- Natural Language Processing: Extracts key preferences from user input
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
- Streamlit Documentation
- Natural Language Processing with Python
- Collaborative Filtering: A Comprehensive Guide
- Building and Deploying Recommendation Systems
- OpenAI. (2025). ChatGPT-03 Mini [Large language model]. OpenAI. https://openai.com
- Anthropic. (2025). Claude [Large language model]. Anthropic. https://www.anthropic.com
- xAI. (2025). Grok [Large language model]. xAI. https://x.ai
- Google. (2025). Gemini [Large language model]. Google DeepMind. https://deepmind.google
This project is licensed under the MIT License - see the LICENSE file for details.
Project Link: https://github.com/sush1998/Xfinity-SmartMatch
⭐ Star us on GitHub — it helps!