动态语义网络用于创造性思维探索
Dynamic semantic networks for exploration of creative thinking
AI总结：
本研究利用动态语义网络量化设计对话中的发散思维，证明其可预测设计想法成功，为实时辅助增强人类创造力提供可能。
摘要：
人类创造力源于大脑皮层网络，这些网络专门负责想法的产生、加工和评估。在设计任务执行过程中，对内心想法进行同步言语化表达，使得动态语义网络能够作为研究、评估和监测创造性思维的工具。使用诸如WordNet这样的词汇数据库，对创造性问题解决中设计想法的收敛或发散进行可复现的信息论量化，其主要优势在于能够同时处理词语和意义，从而能够根据参与概念理解和生成的功能活跃的大脑皮层区域，对所构建的动态语义网络进行解释。在本研究中，通过移动时间窗口计算的语义度量的定量动态变化，在设计评审对话的DTRS10数据集中进行了实证研究，并且检测到的发散思维被证明能够预测设计想法的成功。因此，动态语义网络为创造性问题解决过程中关键事件的实时计算机辅助检测提供了机会，其目标是利用这一知识来人为增强人类创造力。
英文摘要：
Human creativity originates from brain cortical networks that are specialized in idea generation, processing, and evaluation. The concurrent verbalization of our inner thoughts during the execution of a design task enables the use of dynamic semantic networks as a tool for investigating, evaluating, and monitoring creative thought. The primary advantage of using lexical databases such as WordNet for reproducible information-theoretic quantification of convergence or divergence of design ideas in creative problem solving is the simultaneous handling of both words and meanings, which enables interpretation of the constructed dynamic semantic networks in terms of underlying functionally active brain cortical regions involved in concept comprehension and production. In this study, the quantitative dynamics of semantic measures computed with a moving time window is investigated empirically in the DTRS10 dataset with design review conversations and detected divergent thinking is shown to predict success of design ideas. Thus, dynamic semantic networks present an opportunity for real-time computer-assisted detection of critical events during creative problem solving, with the goal of employing this knowledge to artificially augment human creativity.
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。
