Summarizing Non-textual Events with a 'Briefing' FocusRecherche d'Information Assistée par Ordinateur (RIAO), Pittsburgh
Date of Original Version1-1-2007
Abstract or DescriptionWe describe a learning-based system for generating reports based on a mix of text and event data. The system incorporates several stages of processing, including aggregation, template-filling and importance ranking. Aggregators and templates were based on a corpus of reports evaluated by human judges. Importance and granularity were learned from this corpus as well. We find that high-scoring reports (with a recall of 0.89) can be reliably produced using this procedure given a set of oracle features. The report drafting system is part of a learning cognitive assistant RADAR, and is used to describe its performance.
Citation InformationMohit Kumar, Dipanjan Das and Alexander I Rudnicky. "Summarizing Non-textual Events with a 'Briefing' Focus" Recherche d'Information Assistée par Ordinateur (RIAO), Pittsburgh (2007)
Available at: http://works.bepress.com/alexander_rudnicky/45/