University of Illinois Urbana-Champaign

Narrative comprehension through analogy: A study in cognitive modeling and narrative clustering

Wilner, Sean A.

Content Files
WILNER-DISSERTATION-2019.pdf

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https://hdl.handle.net/2142/105624

Description

Title
Narrative comprehension through analogy: A study in cognitive modeling and narrative clustering
Author(s)
Wilner, Sean A.
Issue Date
2019-07-01
Director of Research (if dissertation) or Advisor (if thesis)
Hummel, John E.
Doctoral Committee Chair(s)
Hummel, John E.
Committee Member(s)
  • Girju, Corina R.
  • Hockenmaier, Julia
  • Fisher, Cynthia
Department of Study
Graduate College Programs
Discipline
Informatics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2019-11-26T20:33:45Z
Keyword(s)
  • NLP
  • Analogy
  • Narrative
  • Cognitive Modeling
Abstract
As the field of natural language processing improves and finds its way into everyday use its current limitations and shortcomings become all the more apparent. The next generation of NLP systems will need to be able to handle tasks at a higher level, drawing together information beyond the lexical and across sentence boundaries. To address this need, research into the field of discourse understanding has emerged as a current hot topic with special attention being drawn to narrative comprehension. We explore cognitive modeling and the application of derived measures of analogy to tasks in the discourse/narrative domains. First, we present improvements to the LISA model, a state-of-the-art cognitive model of analogy, increasing the model’s flexibility and robustness, extending the model’s functionality to include a probabilistic measure of belief, and presenting an algorithm for automatically producing the model’s encoding. Finally we test the utility of narrative analogy as a feature for the Story Cloze Task. We find that narrative analogy is a poor feature on its own, but as part of a composite model with sentiment analysis, it outperforms the best task-given baselines but under-performs state-of-the-art. More importantly, through failure analysis we find that narrative analogy, as conceptualized by the field, is insufficient for such tasks, and researchers must first be able to determine when an analogy should be drawn since simply finding all potential analogies proves insufficient.
Graduation Semester
2019-08
Type of Resource
text
Permalink
http://hdl.handle.net/2142/105624
Copyright and License Information
Copyright 2019 Sean Wilner

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