Ontology-Based information and event extraction for business intelligence

Authors:
Ernest Arendarenko;Tuomo Kakkonen
Affiliations:
School of Computing, University of Eastern Finland, Joensuu, Finland;School of Computing, University of Eastern Finland, Joensuu, Finland
Venue:
AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
Year:
2012

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Abstract

We would like to introduce BEECON, an information and event extraction system for business intelligence. This is the first ontology-based system for business documents analysis that is able to detect 41 different types of business events from unstructured sources of information. The described system is intended to enhance business intelligence efficiency by automatically extracting relevant content such as business entities and events. In order to achieve it, we use natural language processing techniques, pattern recognition algorithms and hand-written detection rules. In our test set consisting of 190 documents with 550 events, the system achieved 95% precision and 67% recall in detecting all supported business event types from newspaper texts.