License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.CMN.2015.157
URN: urn:nbn:de:0030-drops-52900
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2015/5290/
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Winston, Patrick Henry

Model-based Story Summary

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Abstract

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.

BibTeX - Entry

@InProceedings{winston:OASIcs:2015:5290,
  author =	{Patrick Henry Winston},
  title =	{{Model-based Story Summary}},
  booktitle =	{6th Workshop on Computational Models of Narrative (CMN 2015)},
  pages =	{157--165},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-93-4},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{45},
  editor =	{Mark A. Finlayson and Ben Miller and Antonio Lieto and Remi Ronfard},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2015/5290},
  URN =		{urn:nbn:de:0030-drops-52900},
  doi =		{10.4230/OASIcs.CMN.2015.157},
  annote =	{Keywords: story telling and summarization, story understanding, cognitive modeling}
}

Keywords: story telling and summarization, story understanding, cognitive modeling
Collection: 6th Workshop on Computational Models of Narrative (CMN 2015)
Issue Date: 2015
Date of publication: 14.08.2015

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