Evaluating Analogy-Based Story Generation: An Empirical Study


  • Jichen Zhu Drexel University
  • Santiago Ontanon Drexel University


Story Generation, Computational Analogy, Evaluation


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.




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