Model-based Story Summary
Name
SummaryCMN15.pdf
Description
Paper as submitted for publication
Size
445.64 KB
Format
Adobe PDF
Checksum (MD5)
bf23ed526d3e30582726025e7f6016bd
Author(s)
Winston, Patrick Henry
Date Issued
May 2015
Journal
Proceedings of the 6th International Workshop on Computational Models of Narrative
Citation
Winston, Patrick Henry. "Model-based Story Summary." 6th International Workshop on Computational Models of Narrative (May 2015).
Version
Author's final manuscript
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 precis 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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
http://drops.dagstuhl.de/opus/volltexte/2015/5290/pdf/19.pdf
