Lexical Creativity from Word Associations

Oskar Gross, Hannu (TT) Toivonen, Jukka M. Toivanen, A. Valitutti
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引用次数: 20

Abstract

A fluent ability to associate tasks, concepts, ideas, knowledge and experiences in a relevant way is often considered an important factor of creativity, especially in problem solving. We are interested in providing computational support for discovering such creative associations. In this paper we design minimally supervised methods that can perform well in the remote associates test (RAT), a well-known psychometric measure of creativity. We show that with a large corpus of text and some relatively simple principles, this can be achieved. We then develop methods for a more general word association model that could be used in lexical creativity support systems, and which also could be a small step towards lexical creativity in computers.
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词汇联想的词汇创造力
以相关的方式将任务、概念、想法、知识和经验流畅地联系起来的能力通常被认为是创造力的重要因素,尤其是在解决问题方面。我们感兴趣的是为发现这种创造性的联系提供计算支持。在本文中,我们设计了最低监督方法,可以在远程联系测试(RAT)中表现良好,这是一种众所周知的创造力心理测量方法。我们表明,使用大量的文本语料库和一些相对简单的原则,这是可以实现的。然后,我们开发了一个更通用的单词关联模型的方法,该模型可以用于词汇创造力支持系统,这也可能是计算机词汇创造力的一小步。
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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