SPEED: a semantics-based pipeline for economic event detection

  • Authors:

  • Frederik Hogenboom;Alexander Hogenboom;Flavius Frasincar;Uzay Kaymak;Otto Van Der Meer;Kim Schouten;Damir Vandicc

  • Affiliations:

  • Erasmus University Rotterdam, Rotterdam, The Netherlands;Erasmus University Rotterdam, Rotterdam, The Netherlands;Erasmus University Rotterdam, Rotterdam, The Netherlands;Erasmus University Rotterdam, Rotterdam, The Netherlands;Erasmus University Rotterdam, Rotterdam, The Netherlands;Erasmus University Rotterdam, Rotterdam, The Netherlands;Erasmus University Rotterdam, Rotterdam, The Netherlands

  • Venue:
  • ER'10 Proceedings of the 29th international conference on Conceptual modeling
  • Year:
  • 2010

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Abstract

Nowadays, emerging news on economic events such as acquisitions has a substantial impact on the financial markets. Therefore, it is important to be able to automatically and accurately identify events in news items in a timely manner. For this, one has to be able to process a large amount of heterogeneous sources of unstructured data in order to extract knowledge useful for guiding decision making processes. We propose a Semantics-based Pipeline for Economic Event Detection (SPEED), aiming to extract financial events from emerging news and to annotate these with meta-data, while retaining a speed that is high enough to make real-time use possible. In our implementation of the SPEED pipeline, we reuse some of components of an existing framework and develop new ones, e.g., a high-performance Ontology Gazetteer and a Word Sense Disambiguator. Initial results drive the expectation of a good performance on emerging news.