creators_name: Mueller, Erik T.
type: preprint
datestamp: 2000-03-01
lastmod: 2011-03-11 08:54:04
metadata_visibility: show
title: Prospects for in-depth story understanding by computer
subjects: comp-sci-art-intel
subjects: ling-comput
full_text_status: public
keywords: story understanding, narrative comprehension
abstract: While much research on the hard problem of in-depth story understanding by computer was performed starting in the 1970s, interest shifted in the 1990s to information extraction and word sense disambiguation. Now that a degree of success has been achieved on these easier problems, I propose it is time to return to in-depth story understanding. In this paper I examine the shift away from story understanding, discuss some of the major problems in building a story understanding system, present some possible solutions involving a set of interacting understanding agents, and provide pointers to useful tools and resources for building story understanding systems.
date: 1999-11
date_type: published
refereed: FALSE
citation:   Mueller, Erik T.  (1999) Prospects for in-depth story understanding by computer.  [Preprint]     
document_url: http://cogprints.org/554/1/storyund.htm