News Monitor: A Framework for Querying News in Real Time

Abstract

News articles generated by online media are a major source of information. In this work, we present News Monitor, a framework that automatically collects news articles from a variety of web pages and performs various analysis tasks. The framework initially identifies fresh news and clusters articles about the same incidents. For every story, it extracts a Knowledge Base (KB) using open information extraction techniques and utilizes this KB in order to build a summary for the user. News Monitor allows the users to query the article in natural language using the state-of-the-art framework BERT. Nevertheless, it allows the user to perform queries also in the KB in order to identify relevant articles. Finally, News Monitor crawls Twitter using a dynamic set of keywords in order to retrieve relevant messages. The framework is distributed, online and performs analysis in real-time.