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Financial News Analysis Using a Semantic Web Approach
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Author(s): Alex Micu (Erasmus University Rotterdam, The Netherlands), Laurens Mast (Erasmus University Rotterdam, The Netherlands), Viorel Milea (Erasmus University Rotterdam, The Netherlands), Flavius Frasincar (Erasmus University Rotterdam, The Netherlands)and Uzay Kaymak (Erasmus University Rotterdam, The Netherlands)
Copyright: 2009
Pages: 18
Source title:
Semantic Knowledge Management: An Ontology-Based Framework
Source Author(s)/Editor(s): Antonio Zilli (University of Salento, Italy), Ernesto Damiani (University of Milan, Italy), Paolo Ceravolo (University of Milan, Italy), Angelo Corallo (University of Salento, Italy)and Gianluca Elia (University of Salento, Italy)
DOI: 10.4018/978-1-60566-034-9.ch015
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Abstract
In this chapter we present StockWatcher, an OWL-based web application that enables the extraction of relevant news items from RSS feeds concerning the NASDAQ-100 listed companies. The application’s goal is to present a customized, aggregated view of the news categorized by different topics. We distinguish between four relevant news categories: i) news regarding the company itself; ii) news regarding direct competitors of the company; iii) news regarding important people of the company; and iv) news regarding the industry in which the company is active. At the same time, the system presented in this chapter is able to rate these news items based on their relevance. We identify three possible effects that a news message can have on the company, and thus on the stock price of that company: i) positive; ii) negative; and iii) neutral. Currently, StockWatcher provides support for the NASDAQ-100 companies. The selection of the relevant news items is based on a customizable user portfolio that may consist of one or more of these companies.
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