Automatic News Summarizer Using TextRank
Rugved Bongale, Talha Chafekar, Mayank Chowdhary, Tushar Bapecha · 2022 IEEE 7th International conference for Convergence in Technology (I2CT) · 2022
Natural Language Processing and Deep Learning have made it possible for machines to understand the text. This is accomplished by comprehending the interrelationships between words and sentences. In this modern era, everyone wants to stay abreast of the latest news but the overwhelming amount of information makes it difficult for one to keep track of the status quo. Hence, we propose a fast summarizer system, with the help of which people can get a glimpse of source-based news summaries. In this system, we extract news from 250 sources and provide them to the user in the form of summaries, which aid in getting a quick overview of the news articles. News is provided in a categorized way where the user can select his favorite new sources. Our system not only effectively summarizes the news articles but also uses caching to ensure faster retrieval and a good user experience. We have chosen a production-efficient algorithm to get quick summaries.