‘Big News’ Morgans: A Chatbot for F1 News Summarization

As the world becomes more digital, people instantly get news on their phones and computers. Thus, they are opting for digital news over newspapers. As news helps us keep up with the activities and events going on around us, it asks for a more creative and sophisticated way to put the relevant news in front of the reader in the form of a news summary; therefore, Text summarization plays a major role in news articles by providing the readers with a summary of the whole article and saving their time and also providing the gist of what the journalist wants to convey. More than news, people love to chit-chat about an event, and in this digital world, we all have our digital friends with whom we can chit-chat, i.e., chatbots. Using a chatbot, people can converse with digital gadgets as though they were conversing with actual people. A bot is a computer program that mimics human interaction (spoken or typed). We plan to build our project using and combining the above-mentioned approaches. We use BERT and T5 as summarises and achieve the highest ROUGE score of 31. We have used Tensorflow to build the neural network for the chatbot and Streamlit to build the UI for the chatbot and host it on the local host server. The news is scraped from Google News using BeautifulSoup.