Model-based Story Summary

Author Patrick Henry Winston

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Patrick Henry Winston

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Patrick Henry Winston. Model-based Story Summary. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 157-165, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


A story summarizer benefits greatly from a reader model because a reader model enables the story summarizer to focus on delivering useful knowledge in minimal time with minimal effort. Such a summarizer can, in particular, eliminate disconnected story elements, deliver only story elements connected to conceptual content, focus on particular concepts of interest, such as revenge, and make use of our human tendency to see causal connection in adjacent sentences. Experiments with a summarizer, built on the Genesis story understanding system, demonstrate considerable compression of an 85-element précis of the plot of Shakespeare’s Macbeth, reducing it, for example, to the 14 elements that make it a concise summary about Pyrrhic victory. Refocusing the summarizer on regicide reduces the element count to 7, or 8% of the original.
  • story telling and summarization
  • story understanding
  • cognitive modeling


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