College of Computing and Digital Media Dissertations

Date of Award

Spring 6-8-2020

Degree Type

Thesis

Degree Name

Master of Science (MS)

School

School of Computing

First Advisor

Raffaella Settimi, PhD

Second Advisor

John Shanahan, PhD

Third Advisor

Jon Gemmell, PhD

Fourth Advisor

Tokunbo Hiamang

Abstract

The primary objective of this thesis is to develop a method that uses machine learning algorithms to enable computational story understanding. This research is conducted with the aim of establishing a system called the Native Storyteller that plans and creates storytelling experiences for human users. The paper first establishes the desired capabilities of the system and then deep dives into how to enable story understanding, which is the core ability the system needs to function. As such, the research places emphasis on natural language processing and its application to solving key problems in this context. Namely, machine representation of story data in a way that adequately respects the contextual information in the story; and, identification of relationships between multiple stories based on this contextual knowledge. To do this, the BookNLP pipeline is used as a backbone for extracting structured data from textual stories sourced from My Book of Bible Stories. The core contribution of this work is the application of extensions beyond the BookNLP pipeline through NLP algorithms and ELMo neural language embeddings to create features that represent the system’s computational understanding of its stories, both at a plot and character-level.

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