In almost all forms of storytelling, the background and the current state of mind of the audience members predispose them to experience a given story from a uniquely personal perspective. However, traditional story writers usually construct their narratives based on the average preferences of their audience, which does not guarantee satisfying narrative experiences for its members. When a narrative aims at providing pleasurable entertainment, having some information about the preferences of the current user for the narrative’s content is vital to create satisfying experiences. This paper explores personality modeling and proposes a novel approach to generate individualized interactive narratives based on the preferences of users, which we model in terms of the Big Five factors. This paper presents and evaluates the proposed method in a web-based interactive storytelling system that explores the Little Red Riding Hood folktale. The results show that the proposed method is capable of correctly recognizing the preferences of users for story events (average accuracy of 91.9%) and positively improve user satisfaction and experience.

在几乎所有形式的讲故事中，观众的背景和当前心态都倾向于使他们从独特的个人角度来体验给定的故事。但是，传统故事作家通常根据受众的平均喜好来构建叙事，这不能保证其成员能够获得令人满意的叙事体验。当叙事旨在提供愉悦的娱乐时，拥有有关当前用户对叙事内容的偏爱的一些信息对于创造令人满意的体验至关重要。本文探讨了人格建模，并提出了一种新颖的方法来根据用户的喜好生成个性化的互动叙事，我们根据五大因素进行建模。本文介绍并评估了在基于网络的交互式讲故事系统中提出的方法，该系统探讨了小红帽的民间故事。结果表明，该方法能够正确识别用户对故事事件的偏好（平均准确度为91.9％），并可以积极提高用户的满意度和体验。