Salience Vectors for Measuring Distance between Stories

Rachelyn Farrell, Mira Fisher, Stephen G. Ware

Research output: Contribution to journalConference articlepeer-review


Narrative planners generate sequences of actions that represent story plots given a story domain model. This is a useful way to create branching stories for interactive narrative systems that maintain logical consistency across multiple storylines with different content. There is a need for story comparison techniques that can enable systems like experience managers and domain authoring tools to reason about similarities and differences between multiple stories or branches. We present an algorithm for summarizing narrative plans as numeric vectors based on a cognitive model of human story perception. The vectors encode important story information and can be compared using standard distance functions to quantify the overall semantic difference between two stories. We show that this distance metric is highly accurate based on human annotations of story similarity, and compare it to several alternative approaches. We also explore variations of our method in an attempt to broaden its applicability to other types of story systems.

Original languageEnglish
Pages (from-to)95-104
Number of pages10
JournalProceedings - AAAI Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE
Issue number1
StatePublished - Oct 11 2022
Event18th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2022 - Pomona, United States
Duration: Oct 24 2022Oct 28 2022

Bibliographical note

Publisher Copyright:
Copyright © 2022, Association for the Advancement of Artificial Intelligence ( All rights reserved.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software


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