An algorithm to generate engaging narratives through non-linearity

Vinay Chilukuri, B. Indurkhya
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引用次数: 3

Abstract

The order in which the events of a story are presented plays an important role in story-telling. In this paper, we present an algorithm that generates narratives of different presentation orders for a story by taking its plan representation and the desired amount of non-linearity as input. We use the principles of event-indexing model, a cognitive model of narrative comprehension, to generate narratives without affecting the ease of comprehension. We hypothesize that a narrative deviated from its chronological order and presented without affecting the ease of comprehension might lead to cognitive engagement. Empirical evaluation of the system was conducted to test this hypothesis along with the amount of non-linearity that could be introduced in a story without affecting the ease of comprehension.
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一种通过非线性产生引人入胜的叙事的算法
故事事件呈现的顺序在讲故事中起着重要的作用。在本文中,我们提出了一种算法,该算法通过将故事的计划表示和所需的非线性量作为输入,为故事生成不同呈现顺序的叙述。我们使用事件索引模型的原则,即一种叙事理解的认知模型,在不影响理解的情况下生成叙事。我们假设,在不影响理解的情况下,偏离时间顺序的叙述可能会导致认知参与。我们对该系统进行了实证评估,以检验这一假设,以及在不影响理解难度的情况下可以在故事中引入的非线性量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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HT '22: 33rd ACM Conference on Hypertext and Social Media, Barcelona, Spain, 28 June 2022- 1 July 2022 HT '21: 32nd ACM Conference on Hypertext and Social Media, Virtual Event, Ireland, 30 August 2021 - 2 September 2021 HT '20: 31st ACM Conference on Hypertext and Social Media, Virtual Event, USA, July 13-15, 2020 Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides. QualityRank: assessing quality of wikipedia articles by mutually evaluating editors and texts
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