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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.