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SPEED: A Semantics-Based Pipeline for Economic Event Detection

  • Frederik Hogenboom
  • Alexander Hogenboom
  • Flavius Frasincar
  • Uzay Kaymak
  • Otto van der Meer
  • Kim Schouten
  • Damir Vandic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6412)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Frederik Hogenboom
    • 1
  • Alexander Hogenboom
    • 1
  • Flavius Frasincar
    • 1
  • Uzay Kaymak
    • 1
  • Otto van der Meer
    • 1
  • Kim Schouten
    • 1
  • Damir Vandic
    • 1
  1. 1.Erasmus University RotterdamRotterdamThe Netherlands

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