Information Extraction of Corporate Events from the Web скачать в хорошем качестве

Information Extraction of Corporate Events from the Web

Information Extraction of Corporate Events from the Web Presenters: Tianxiao Jiang, David Li, Liren Wu Project Mentor: Yuval Marton & Swapnil Khedekar, Bloomberg Abstract: Publicly traded companies are required to report earnings and hold certain types of events. During these events stocks are most volatile and draw huge interests from analysts, investors, shareholders and journalists. Therefore collecting this information is valuable, but the problem in extracting this information is that companies announce their events on the web in various ways and formats. We are building a pipeline that extracts key information, such as the event type, date, and time, from corporate event announcements on websites. This extracted data is then normalized so it can be easily used later. We are using a variety of natural language processing techniques ranging from rule-based or regular expression based approaches to Transformer-based techniques such as BERT and GPT to extract events from websites, normalize the data, and classify the type of these events.