Learning to Extract Security-related Event Information from Large News Collections

author: Hristo Tanev, Joint Research Centre
published: Dec. 3, 2007,   recorded: September 2007,   views: 3515


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Automatic Event Extraction from texts emerges as an im- portant and complex text mining task. Its goal is to detect description of events of a speci¯c type described in the text. For each event the Event Extraction system is expected to ¯nd the time, the location, the participants in this event and their roles, as well as other related circum- stances. In this talk we present a Machine Learning approach for learning of information extraction patterns, a method for semi-automatic lexical acquisition, and an information aggregation strategy implemented in a working prototype nexus which detects automatically security related events in clusters of news articles.

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