Abstract
Gathering news events on companies to provide business
intelligence to financial investors and creditors is a challenging
problem. With a plethora of online news providers and tens of thousands of
companies to monitor, automating the extraction and fusion of events is
crucial. We developed an intelligent agent-based component framework to
query and extract events from multiple providers. This framework
integrates multiple machine learning and natural language processing
techniques to down-select articles and extract targeted events. Results
indicate that our system is capable of extracting focal events on a
variety of topics with effective precision and recall.
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