https://github.com/amri-tah/leetpath
A graph-based personalized LeetCode question recommender that uses probabilistic reasoning and topic modeling for skill enhancement.
https://github.com/amri-tah/leetpath
flask go leetcode leetcode-problem-recommendation-system leetcode-problem-recommender leetcode-recommender nextjs problem-recommender recommender
Last synced: 7 months ago
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A graph-based personalized LeetCode question recommender that uses probabilistic reasoning and topic modeling for skill enhancement.
- Host: GitHub
- URL: https://github.com/amri-tah/leetpath
- Owner: amri-tah
- License: mit
- Created: 2024-10-22T16:00:50.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-17T15:35:02.000Z (9 months ago)
- Last Synced: 2025-01-17T16:47:05.199Z (9 months ago)
- Topics: flask, go, leetcode, leetcode-problem-recommendation-system, leetcode-problem-recommender, leetcode-recommender, nextjs, problem-recommender, recommender
- Language: JavaScript
- Homepage: https://leetpath.vercel.app
- Size: 55 MB
- Stars: 5
- Watchers: 1
- Forks: 8
- Open Issues: 2
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# **LeetPath: A Graph-Based LeetCode Question Recommender 🧭🔍**
LeetPath is a personalized question recommendation system designed for LeetCode users. Using graph-based structures, topic modeling, and Markov Random Field, the system analyzes user interaction, question similarity, and topic relevance to suggest the most appropriate questions for continued skill improvement. 📈
## **Demo 🎥**
https://github.com/user-attachments/assets/c13063e2-c943-4b51-b664-545248d37f06
## **Features 🌟**
- 🔍 Personalized Recommendations: Suggests questions based on user activity and skills.
- 🧠 Topic Modeling: Groups questions by related topics for better understanding.
- 📊 Interactive Dashboard: Displays user stats and recommended questions.
- ⚡ Real-Time Performance: Fast and efficient recommendations using graph-based algorithms and belief propagation.
## **Tech Stack 🛠️**
- **Frontend**: Next.js with Tailwind CSS for a responsive and interactive UI.
- **Backend**: **Flask** for API endpoints for the model and Go for fetching user data.
- **Database**: **MongoDB** for storing user data.
- **Authentication**: **Firebase** for secure user login and management.
- **GraphQL**: For efficient and flexible data querying.
## **Deployment and Hosting 💻**
- The recommendation engine is deployed on **Google Cloud Platform** using **App Engine**.
- The backend code is deployed on **OnRender**.
- The frontend is hosted on **Vercel**.
## **How It Works** 📊
- Question Similarity: Content-based filtering using TF-IDF and cosine similarity to recommend questions based on their content similarity.
- Topic Modeling: Grouping questions by latent topics using a custom topic modeling algorithm (similar to Latent Dirichlet Allocation).
- Markov Random Field (MRF): Models relationships between questions, accounting for user engagement, difficulty, and question similarities.
- Belief Propagation: Used to refine potential values in the MRF and improve recommendation accuracy.
## Screenshots
### Contributors
@VishalTheHuman
@amri-tah
@yeager209904
@GiriPrasath017
Vishal S
Amritha Nandini
Anerud Thiyagarajan
Giri Prasath R
## Contributing 🌟
We welcome contributions to enhance the functionality of LeetPath! If you have ideas or improvements, please submit a pull request . 🚀
## License 📜
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details . 📄
## Contact 📧
For any queries or support, please contact us at [amrithanandini2003@gmail.com](mailto:amrithanandini2003@gmail.com) or [vishalatmadurai@gmail.com](mailto:vishalatmadurai@gmail.com). We're here to help you!📬
Thank you for using LeetPath! Let's elevate your LeetCode experience together. 🚀💻