Using Explicit Semantic Models to Track Situations across News Articles

Earl J Wagner, Jiahui Liu, Larry Birnbaum, Kenneth D. Forbus, James Baker

Online news is a rich information resource for learning about new, ongoing, and past events. Intelligence analysts, news junkies, and ordinary people all track developments in ongoing situations as they unfold over time and initiate queries to learn more about the past context of the events of interest to them. Brussell/STT (Situation Tracking Testbed) is an intelligent information system aimed at supporting this activity. Brussell employs a combination of explicit semantic models, information retrieval (IR), and information extraction (IE) in order to track a situation. It finds relevant news stories, organizes those stories around the aspects of the situation to which they pertain, and extracts certain basic facts about the situation for explicit representation. Brussell uses scripts as situation models for the episodes it tracks. Script instances are represented in CycL and stored in the Cyc knowledge-base. Models of ongoing situations can be reloaded and updated with new information as desired.

Subjects: 1. Applications

Submitted: May 30, 2006

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