🔍 LSI Search System

A web application that enables semantic document search using Latent Semantic Indexing (LSI). The system preprocesses text, computes TF-IDF, applies Singular Value Decomposition (SVD) for dimensionality reduction, and retrieves documents based on cosine similarity.

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🚀 Features

• Preprocessing: Removes stopwords and applies stemming/lemmatization.
• TF-IDF Computation: Converts documents into numerical vectors.
• SVD Decomposition: Reduces dimensionality to enhance semantic search.
• Cosine Similarity: Ranks documents by relevance to the search query.
• Flask API: Handles search requests and retrieves relevant documents.
• React Frontend: Provides a user-friendly interface for searching.

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📂 Project Structure

📁 vwm
│
├── 📁 backend
│ ├── server.py # 🏗️ Flask backend API
│ ├── db.py # 🍃 MongoDB database connection
│ ├── preprocess.py # ✂️ Text preprocessing
│ ├── TF-IDF.py # 🔢 TF-IDF computation
│ ├── SVD.py # 🔍 Singular Value Decomposition
│ └── cosineSimilarity.py # 📐 Cosine similarity computation
│
├── 📁 frontend
│ └── 📁 src
│ ├── pages/Home.js # 🔍 Search input and results display
│ ├── App.js # ⚛️ React app configuration
│ ├── pages/home.css # 🎨 Styling for UI │ └── App.css' # 🎨 Styling for UI │
├── app.py # 🚀 Runs both frontend & backend
└── README.md # 📖 Project documentation

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🛠 Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/FirstOne96/LSI-Search-System.git
cd vwm

2️⃣ Setup Backend (Flask)

cd backend
python -m venv venv  # Create a virtual environment
source venv/bin/activate  # Activate virtual environment (Mac/Linux)
venv\bin\activate  # Activate virtual environment (Windows)
pip install -r requirements.txt  # Install dependencies

3️⃣ Setup Frontend (React)

cd ../frontend
rm -rf node_modules package-lock.json
npm cache clean --force
npm install
npm install --save-dev eslint-config-react-app eslint@latest
npm install eslint@^8.0.0 --save-dev
npm install eslint-config-react-app@latest --save-dev
npm start

4️⃣ Start the Project

cd ..
python app.py  # Runs both backend & frontend

🖥️ Technologies Used

Backend

• 🐍 Flask – Web framework
• 🍃 MongoDB – NoSQL database
• ✂ NLTK – Text processing
• 🔢 Scikit-learn – TF-IDF, SVD

Frontend

• ⚛ React – UI framework
• 🎨 Tailwind CSS – Styling

🤝 Contributing

Feel free to fork this repository and submit a pull request with improvements!