Development of a natural language processing system for automated content summarization
Table Of Contents
<p>1. Introduction<br> 1.1 Background<br> 1.2 Motivation<br> 1.3 Objectives<br>2. Literature Review<br> 2.1 Text summarization techniques<br> 2.2 NLP and machine learning for content analysis<br>3. System Architecture<br> 3.1 Text preprocessing and feature extraction<br> 3.2 Summarization algorithms and models<br> 3.3 User interface design<br>4. NLP Techniques<br> 4.1 Sentence and document representation<br> 4.2 Extractive and abstractive summarization methods<br>5. Implementation<br> 5.1 NLP libraries and frameworks<br> 5.2 System integration and testing<br></p>
Thesis Abstract
<p> This project aims to develop a natural language processing (NLP) system for automated content summarization. The system will utilize NLP techniques, machine learning algorithms, and text summarization methods to automatically generate concise and coherent summaries of large textual documents. The project will focus on designing and implementing an NLP system that can accurately extract essential information from diverse sources and produce high-quality summaries for various applications. <br></p>Thesis Overview
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