应用文本挖掘分析创造力研究中的人类提问行为
Applying Text Mining to Analyze Human Question Asking in Creativity Research
AI总结：
本研究应用文本挖掘方法衡量问题的认知潜力，考虑问题类型、复杂性和答案内容，提出新方法并在五个数据集上验证，表明自然语言处理在创造力研究中具有重要作用。
摘要：
创造力与在感兴趣领域产生新颖且有效想法的能力相关。这些创造性想法是如何产生的？一个支持创造性思维并日益受到实证关注的可能机制是提问。提问是一种可能的认知机制，有助于定义问题，促进创造性问题解决。然而，关于问题在创造力中的确切作用，仍有许多未知之处。本研究尝试应用文本挖掘方法来衡量问题的认知潜力，并综合考虑（a）问题类型、（b）问题复杂性和（c）答案内容等因素。本文综述了作为创造力研究一部分的问题挖掘的历史，以及被认为在研究中有用或有益的自然语言处理方法。此外，提出了一种新方法，并将其应用于五个数据集。对所得实验结果进行了全面分析，表明自然语言处理在创造性研究中可以发挥作用。
英文摘要：
Creativity relates to the ability to generate novel and effective ideas in the areas of interest. How are such creative ideas generated? One possible mechanism that supports creative ideation and is gaining increased empirical attention is by asking questions. Question asking is a likely cognitive mechanism that allows defining problems, facilitating creative problem solving. However, much is unknown about the exact role of questions in creativity. This work presents an attempt to apply text mining methods to measure the cognitive potential of questions, taking into account, among others, (a) question type, (b) question complexity, and (c) the content of the answer. This contribution summarizes the history of question mining as a part of creativity research, along with the natural language processing methods deemed useful or helpful in the study. In addition, a novel approach is proposed, implemented, and applied to five datasets. The experimental results obtained are comprehensively analyzed, suggesting that natural language processing has a role to play in creative research.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
