模糊链接图：创意活动轨迹的自动图形化摘要
Fuzzy Linkography: Automatic Graphical Summarization of Creative Activity Traces
AI总结：
本文提出模糊链接图方法，利用模糊语义相似性自动从设计动作序列构建链接图，应用于三类创意轨迹，实现规模化评估并探讨其优势与局限。
摘要：
链接图——对构成一段创意构思或设计过程的设计动作之间链接的分析——可用于创意活动轨迹的视觉和定量评估。然而，传统链接图耗时费力，需要人工编码员手动标注一段过程中的设计动作及其之间的连接。因此，链接图尚未大规模应用。为解决这一局限，我们引入了模糊链接图：一种通过“模糊”语义相似性计算模型，从一系列记录的设计动作中自动构建链接图的方法，从而支持链接图技术的更广泛部署和新应用。我们将模糊链接图应用于三种截然不同的创意活动轨迹（文生图提示旅程、大语言模型支持的构思会话以及研究者发表历史），并讨论了我们的发现、方法的优势、局限性及潜在未来应用。
英文摘要：
Linkography -- the analysis of links between the design moves that make up an episode of creative ideation or design -- can be used for both visual and quantitative assessment of creative activity traces. Traditional linkography, however, is time-consuming, requiring a human coder to manually annotate both the design moves within an episode and the connections between them. As a result, linkography has not yet been much applied at scale. To address this limitation, we introduce fuzzy linkography: a means of automatically constructing a linkograph from a sequence of recorded design moves via a "fuzzy" computational model of semantic similarity, enabling wider deployment and new applications of linkographic techniques. We apply fuzzy linkography to three markedly different kinds of creative activity traces (text-to-image prompting journeys, LLM-supported ideation sessions, and researcher publication histories) and discuss our findings, as well as strengths, limitations, and potential future applications of our approach.
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。
