Story Similarity Data Set
Authors:
- Rachelyn Farrell
- Mira Fisher
- Stephen G. Ware
Date Archived:
24 October 2022
Accompanying Paper:
Salience Vectors for Measuring Distance Between Stories
Alternative URL:
http://cs.uky.edu/~sgware/projects/storysimilarity/index.php
Description:
58 stories were generated by a narrative planner (an algorithm for telling multi-agent stories). 64 subjects were shown a reference story and two other stories, labeled A and B. Subjects were asked to choose whether story A or B was more similar to the reference story. Subjects were shown the English translations of the stories.
How to Cite This Artifact
The examples below show how to cite this page, but when referring to this work, many authors will prefer that you cite the accompanying paper linked above.
AAAI Style
Farrell, R.; Fisher, M.; and Ware, S. G. 2022. Story Similarity Data Set. http://aiide.org/artifacts/story_similarity_data_set. Accessed 23 December 2024.
IEEE Style
R. Farrell, M. Fisher, and S. G. Ware, "Story Similarity Data Set," 2022. [Online]. Available: http://aiide.org/artifacts/story_similarity_data_set. [Accessed Dec 23, 2024].
BiBTeX Entry
@misc{story_similarity_data_set, author={Farrell, Rachelyn and Fisher, Mira and Ware, Stephen G.}, title={Story Similarity Data Set}, howpublished={\url{http://aiide.org/artifacts/story_similarity_data_set}}, year={2022}, note={Accessed 23 December 2024} }