Quora Duplicate Question Pairs Detector

🔍 Overview

This Streamlit web application predicts whether two questions from Quora are duplicates, aiming to reduce redundancy and enhance user experience on Q&A platforms. By leveraging Natural Language Processing (NLP) techniques and machine learning models, the app provides real-time predictions on question similarity.

🧠 Features

• User-Friendly Interface: Input two questions and receive instant feedback on their similarity.
• Preprocessing Pipeline: Includes text cleaning, stopword removal, and vectorization using Bag of Words (BoW).
• Machine Learning Model: Utilizes a trained model (e.g., Logistic Regression) to predict duplicate questions.

🗂 Project Structure

├── app.py # Main Streamlit application
├── helper.py # Helper functions for preprocessing
├── model.pkl # Trained ML model
├── cv.pkl # CountVectorizer object
├── stopwords.pkl # List of stopwords
├── requirements.txt # Python dependencies
└── README.md # Project documentation

🚀 Getting Started

Would recommend using powershell/windows for streamlit apps .

Prerequisites

• Python 3.7 or higher
• pip (Python package installer)

Installation & Setup

1. Clone the repository:

   https://github.com/vennelavarshini18/Quora-Duplicate-Question-Pairs-Detector.git

2. Navigate to the project directory:

   cd Quora-Duplicate-Question-Pairs-Detector 

3. Create a virtual environment (optional but recommended):

   python -m venv venv

4. Activate the virtual environment:
   • Windows:

     venv\Scripts\activate

   • Mac/Linux:

     source venv/bin/activate

5. Install the required dependencies:

   pip install -r requirements.txt

Running the Application

After installation, follow these steps to run the project:

1. Start the application:

   streamlit run app.py

2. Open your browser and go to:

   https://127.0.0.1:5000/
   

   (or the address displayed in your terminal)

📈 Model Details

• Vectorization: Bag of Words (BoW) using CountVectorizer
• Model: Logistic Regression trained on preprocessed question pairs
• Evaluation Metric: Accuracy score on a validation set

📚 References

• Quora Question Pairs Dataset on Kaggle
• Stanford CS224n Report

🤝 Contributing

Contributions are welcome! Please fork the repository and submit a pull request for any enhancements or bug fixes.