Authoring support by interactive genetic algorithm and case based retrieval

Ken Kuriyama, T. Terano, M. Numao
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引用次数: 11

Abstract

Authoring work for multimedia contents is knowledge-lean work. Elementary school pupils frequently have difficult acquiring authoring skills, i.e. how to develop the idea or materials to be expressed, how to compose the materials of the outcome or contents. We focus on the problems of how to support authoring work to arrange materials in order to formulate ideas as the stories develop. The basic ideas behind the method are that (1) a basic story is automatically generated by genetic algorithm (GA) based operations and shown to a user as sequences of pictures, (2) an interactive GA is used to evaluate and select a preferred story, (3) the results are compared with previously stored stories using case-based techniques. Based on these ideas, we have developed a computer supported environment for this purpose and conducted related experiments.
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交互式遗传算法和基于案例的检索支持创作
多媒体内容创作工作是一项知识精益工作。小学生通常很难获得写作技能,即如何发展要表达的想法或材料,如何组成结果或内容的材料。我们关注的问题是如何支持创作工作来安排材料,以便随着故事的发展形成想法。该方法背后的基本思想是:(1)基于遗传算法(GA)的操作自动生成基本故事并作为图片序列显示给用户;(2)使用交互式遗传算法来评估和选择首选故事;(3)使用基于案例的技术将结果与先前存储的故事进行比较。基于这些想法,我们为此开发了一个计算机支持的环境,并进行了相关的实验。
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