-20%

Question Generation from Text

0 Orders 0 Wish listed

₹4,999.00

Qty

Total price:

₹4,999.00

Overview
Reviews

Detail Description

1. Abstract

Question Generation from Text is an AI-based system that automatically generates meaningful questions from input text using Natural Language Processing (NLP) and machine learning techniques. The system analyzes the given content, identifies important information, and creates relevant questions for learning, revision, and assessment. It helps teachers prepare quizzes, supports students in self-assessment, and reduces the time required to create educational questions manually.

2. Objectives

Automatically generate questions from text.
Identify important concepts and key information.
Generate relevant questions from paragraphs and documents.
Support educational assessments and learning activities.
Reduce the manual effort involved in question preparation.

3. Existing System

Traditional question preparation requires teachers or content creators to read educational materials and manually formulate questions. This process can be time-consuming and may limit the number of questions generated from large amounts of text.

Disadvantages

Requires significant manual effort.
Takes time to prepare questions from lengthy documents.
May produce limited question variety.
Makes large-scale quiz preparation difficult.

4. Proposed System

The proposed system uses NLP techniques and AI language models to analyze input text and generate questions automatically. Users can enter text or upload supported documents, select the number or type of questions, and receive questions based on the provided content. Advanced versions can generate multiple-choice, short-answer, and comprehension questions with optional answers.

5. Implementation Procedure

Develop an interface for entering text or uploading documents.
Extract text from supported file formats.
Preprocess the text by removing unnecessary content.
Identify important sentences, keywords, and concepts.
Apply an NLP model or transformer-based question-generation model.
Generate questions based on the input content.
Optionally generate answers and multiple-choice options.
Display the generated questions to the user.
Evaluate question relevance, clarity, and factual accuracy.

6. Software Requirements

Programming Language: Python
Frontend: Streamlit or HTML, CSS, and JavaScript
NLP Libraries: NLTK, spaCy, or Transformers
AI Models: T5, BART, or a suitable LLM
Document Processing: PyMuPDF or python-docx
Data Processing: Pandas and NumPy
Development Environment: VS Code or Jupyter Notebook
Operating System: Windows, Linux, or macOS

7. Hardware Requirements

Processor: Intel Core i3 or equivalent and above
RAM: Minimum 4 GB; 8 GB recommended
Storage: At least 5 GB of free space
GPU: Optional, depending on the model used
Internet: Required for cloud-based AI models and APIs

8. Advantages of the Project

Generates questions quickly from educational content.
Reduces manual question preparation.
Supports different question formats.
Helps students revise important concepts.
Assists teachers in preparing quizzes and assessments.
Can process content from multiple supported document formats.

No review given yet!

Fast Delivery all across the country

Safe Payment

7 Days Return Policy

100% Authentic Products

Shopping cart