NLP-Based Summary Generator

Developed an application using Natural Language Processing (NLP) to automatically generate text summaries and related questions. The project extracts key information from documents, providing concise overviews and practice questions for better understanding. Built with Flask for the back-end and integrates NLP models for text analysis and content generation.

Categories

Web App

Client

Final Year Project

In today’s digital world, users deal with large amounts of textual information (articles, research papers, news, etc.). Reading long documents is time-consuming.

The system allows users to:

  • Input long text

  • Generate automatic summaries

  • Store and manage summaries in a database

  • Optionally generate questions from the summarized text

  • PDF file upload

System Architecture

Frontend (HTML, CSS, Bootstrap)

  • User inputs text.
  • Displays generated summary
  • Displays generated questions


Backend (Flask)

  • Handles HTTP requests
  • Calls NLP processing functions
  • Connects to database

NLP Module

  • Text preprocessing
  • Tokenization
  • Stopword removal
  • Sentence scoring
  • Summary generation

Database (PostgreSQL)

  • Original text
  • Generated summaries
  • Timestamp

This project demonstrates the effective integration of Natural Language Processing (NLP) techniques with modern web development technologies to build a practical and intelligent text summarization system. By combining Python-based NLP processing with a Flask backend and a PostgreSQL database, the application transforms long textual content into concise and meaningful summaries. The project highlights the ability to apply core NLP concepts such as text preprocessing, tokenization, stopword removal, and sentence scoring, while also showcasing full-stack development skills through the design of a user-friendly web interface and backend logic. Furthermore, it demonstrates competence in database management for storing and retrieving processed data, as well as the development of real-world AI-driven applications that address practical problems such as information overload and time-efficient reading.

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