News Summarization of BBC Articles: A Multi-Category Approach

Abstract

In this research project, we explore the application of advanced natural language processing techniques to automatically summarize news articles from the BBC. The dataset comprises five distinct categories— business, entertainment, politics, sport, and tech—each containing a wealth of information. Our primary goal is to develop an efficient and accurate news summarization system using state-of-the-art language models. We employ the Hugging Face Transformers library to create a summarization pipeline capable of extracting key information from lengthy news articles.