computational analogy
On the Role of Domain Knowledge in Analogy-Based Story Generation
Ontanon, Santiago (IIIA-CSIC) | Zhu, Jichen (University of Central Florida)
Computational narrative is a complex and interesting domain for exploring AI techniques that algorithmically analyze, understand, and most importantly, generate stories. This paper studies the importance of domain knowledge in story generation, and particularly in analogy-based story generation (ASG). Based on the construct of knowledge container in case-based reasoning, we present a theoretical framework for incorporating domain knowledge in ASG. We complement the framework with empirical results in our existing system Riu.
Story and Text Generation through Computational Analogy in the Riu System
Ontanon, Santiago (Artificial Intelligence Research Institute, IIIA-CSIC Barcelona, Spain) | Zhu, Jichen (Department of Digital Media University of Central Florida (UCF) Orlando, USA)
A key challenge in computational narrative is story generation. In this paper we focus on analogy-based story generation, and, specifically, on how to generate both story and text using analogy. We present a dual representation formalism where a human-understandable representation (composed of English sentences) and a computer-understandable representation (consisting in a graph) are linked together in order to generate both story and natural language text by analogy. We have implemented our technique in the Riu interactive narrative system.