Thesis Abstract

This project aims to develop a natural language processing (NLP) system for automated content summarization that can generate concise and coherent summaries of textual content. The system will leverage NLP techniques, such as text summarization algorithms, semantic analysis, and language modeling, to automatically extract key information from documents, articles, and other textual sources. The project will address the challenges of automated content summarization, such as information extraction, coherence, and readability, by designing and implementing an NLP system that can produce high-quality and informative summaries across diverse content domains.

Thesis Overview