Using explicit semantic models to track situations across news articles

Earl J. Wagner*, Liu Jiahui, Lawrence A Birnbaum, Kenneth D Forbus, James Baker

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationEvent Extraction and Synthesis - Papers from the AAAI Workshop, Technical Report
Number of pages6
StatePublished - 2006
Event2006 AAAI Workshop - Boston, MA, United States
Duration: Jul 16 2006Jul 20 2006

Publication series

NameAAAI Workshop - Technical Report


Other2006 AAAI Workshop
Country/TerritoryUnited States
CityBoston, MA

ASJC Scopus subject areas

  • Engineering(all)


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