In this report, we present our research results during the fourth half-year- phase of the project Corporate Smart Content under the working package ”Knowledge-based Mining of Complex Event Patterns”. We present here a novel approach for real-time extraction of news, based on user specifications and by using background knowledge from specific news domains. We create a powerful filtering service which limits the news data to the concrete and essential preferences of a user. In our approach, enrichment of real- time news with background knowledge is a preprocessing step. We use a Complex Event Processor to detect complex events from the enriched articles and match them to the user specified query. Each time a news article is matched, its result is notified to the user immediately. Our experimental evaluation shows that our approach is feasible for detecting news in real- time with high precision and recall.
