Semantics-based information extraction for detecting economic events

  • Authors:

  • Alexander Hogenboom;Frederik Hogenboom;Flavius Frasincar;Kim Schouten;Otto Meer

  • Affiliations:

  • Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000 DR;Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000 DR;Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000 DR;Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000 DR;Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands 3000 DR

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2013

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Abstract

As today's financial markets are sensitive to breaking news on economic events, accurate and timely automatic identification of events in news items is crucial. Unstructured news items originating from many heterogeneous sources have to be mined in order to extract knowledge useful for guiding decision making processes. Hence, we propose the Semantics-Based Pipeline for Economic Event Detection (SPEED), focusing on extracting financial events from news articles and annotating these with meta-data at a speed that enables real-time use. In our implementation, we use some components of an existing framework as well as new components, e.g., a high-performance Ontology Gazetteer, a Word Group Look-Up component, a Word Sense Disambiguator, and components for detecting economic events. Through their interaction with a domain-specific ontology, our novel, semantically enabled components constitute a feedback loop which fosters future reuse of acquired knowledge in the event detection process.