SPEED: A Semantics-Based Pipeline for Economic Event Detection

Frederik Hogenboom, Alexander Hogenboom, Flavius Frasincar, U Kaymak, O v.d. Meer, Kim Schouten, Damir Vandic

Research output: Contribution to conferencePosterAcademic

7 Citations (Scopus)


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.
Original languageEnglish
Number of pages6
Publication statusPublished - 1 Nov 2010
EventTwenty-Ninth International Conference on Conceptual Modeling (ER 2010) - Vancouver, British Columbia, Canada
Duration: 1 Nov 20104 Nov 2010


ConferenceTwenty-Ninth International Conference on Conceptual Modeling (ER 2010)
CityVancouver, British Columbia, Canada


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