ICIDS 2013: Interactive Storytelling pp 95-106 | Cite as

Towards Automatic Story Clustering for Interactive Narrative Authoring

  • Michal Bída
  • Martin Černý
  • Cyril Brom
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8230)

Abstract

Interactive storytelling systems are capable of producing many variants of stories. A major challenge in designing storytelling systems is the evaluation of the resulting narrative. Ideally every variant of the resulting story should be seen and evaluated, but due to combinatorial explosion of the story space, this is unfeasible in all but the smallest domains. However, the system designer still needs to have control over the generated stories and his input cannot be replaced by a computer. In this paper we propose a general methodology for semi-automatic evaluation of narrative systems based on tension curve extraction and clustering of similar stories. Our preliminary results indicate that a straightforward approach works well in simple scenarios, but for complex story spaces further improvements are necessary.

Keywords

Multiagent System Jaccard Index Tension Curve Action String Play Session 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Michal Bída
    • 1
  • Martin Černý
    • 1
  • Cyril Brom
    • 1
  1. 1.Faculty of Mathematics and PhysicsCharles University in PraguePragueCzech Republic

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