Evaluating Analogy-Based Story Generation: An Empirical Study

Authors

  • Jichen Zhu Drexel University
  • Santiago Ontanon Drexel University

Keywords:

Story Generation, Computational Analogy, Evaluation

Abstract

Evaluation is one of the major open problems in computational narrative. In this paper, we present an empirical study of SAM, an analogy-based story generation (ASG) algorithm, that was created as part of our Riu interactive narrative system. Specifically, our study focuses on SAM's capability to retrieve and generate short non-interactive stories. Combining qualitative and quantitative methods from different disciplines, the methodology in this study can be extended to evaluating other computational narrative systems.

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Published

2021-06-30

How to Cite

Zhu, J., & Ontanon, S. (2021). Evaluating Analogy-Based Story Generation: An Empirical Study. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 9(1), 198-204. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/12674