Research Article Search Engine

A robust and efficient search engine designed to index and query a database of 5 million research articles. This project leverages modern web technologies for a seamless user experience and high-performance search capabilities.

Data Source Link: https://www.kaggle.com/datasets/agungpambudi/research-citation-network-5m-papers?select=dblp-citation-network-v14.json

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Current Status

• Data Preprocessing
• Forward Indexing
• Reverse Indexing

🌟 Features

• Responsive Frontend:

  • Built with Next.js for dynamic rendering, fast performance, and SEO optimization.
  • Intuitive user interface to quickly find relevant articles.

• High-Performance Backend:

  • Powered by Python Flask, providing robust APIs for search queries and metadata retrieval.
  • Scalable architecture to handle a large dataset and concurrent users.

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📂 Project Structure

Frontend

• Framework: Next.js
• Features:
  • Server-side rendering for fast page loads.
  • Modular and reusable components.
  • Integrated with backend APIs for real-time search and data visualization.

Backend

• Framework: Python Flask
• Features:
  • RESTful API endpoints for efficient querying.
  • Optimized database indexing for search performance.
  • Pagination and caching for better user experience.

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🚀 Setup and Installation

Prerequisites

• Node.js v16+ and npm
• Python