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Post-recommendation-system

This project is an NLP-based intelligent post recommendation system built with Python, Streamlit, spaCy, TF-IDF, cosine similarity, and SQLite database.

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🧐 Intelligent Post Recommendation System

This project is an NLP-based intelligent post recommendation system built with Python, Streamlit, spaCy, TF-IDF, cosine similarity, and SQLite database.

It allows users to add posts, fetch similar posts based on a query, and view all posts in the database.

🚀 Features

  • Intelligent recommendation of similar posts based on user query.
  • Add new posts through a simple web UI.
  • View all posts stored in a database.
  • Preprocessing using spaCy (lemmatization, stopword removal).
  • TF-IDF vectorization and cosine similarity for recommendations.
  • SQLite database for storage.
  • Easy-to-run with Streamlit app interface.

🛠️ Technologies Used

  • Python 3.x
  • Streamlit
  • spaCy (en_core_web_sm)
  • scikit-learn (TF-IDF + cosine similarity)
  • SQLite (built-in DB)
  • Pandas

📆 Installation

First, clone the repository or copy the code files:

bash git clone https://github.com/nabeel03103n/Post-recommendation-system.git cd post-recommendation-system

Install the required dependencies:

bash pip install streamlit spacy scikit-learn pandas python -m spacy download en_core_web_sm

📂 Project Structure

post-recommendation-system/ ├── app.py # Main Streamlit app ├── seed_posts.py # (Optional) Script to populate database with 1000+ posts ├── posts.db # SQLite database file (auto-created) └── README.md # Project documentation

⚡ Running the Application

  1. Start the Streamlit server:

bash streamlit run app.py

  1. It will open automatically in your browser at: http://localhost:8501

📝 Usage

  • Recommend: Enter a query/post idea, and get top similar posts.
  • Add Post: Add new posts manually through the UI.
  • View All Posts: See all stored posts in a table view.

If you want to preload 1000+ sample posts:

bash python seed_posts.py

Then refresh your app.

🧀 Example Queries

  • "Deploy an AI chatbot using Python."
  • "Learn computer vision with OpenCV."
  • "Introduction to blockchain technology."
  • "Master deep learning best practices."

🌟 Future Improvements (Ideas)

  • Add categories/tags for better filtering.
  • Enable user authentication (login/signup).
  • Migrate database to PostgreSQL/MySQL for production.
  • Improve UI using Streamlit Components or Tailwind + Streamlit.

🤝 Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

📄 License

This project is licensed under the MIT License.

Built with ❤️ using Python and Streamlit.