Effective communication of UX considerations to stakeholders (e.g., designers and developers) is a critical challenge for UX practitioners. To explore this problem, we interviewed four UX practitioners about their communication challenges and strategies. Our study identifies that providing an example user flow-a screen sequence representing a semantic task-as evidence reinforces communication, yet finding relevant examples remains challenging. To address this, we propose a method to systematically retrieve user flows using semantic embedding. Specifically, we design a model that learns to associate screens' visual features with user flow descriptions through contrastive learning. A survey confirms that our approach retrieves user flows better aligned with human perceptions of relevance. We analyze the results and discuss implications for the computational representation of user flows.

翻译：向利益相关者（如设计师和开发者）有效传达用户体验（UX）考量，是UX从业者面临的一项关键挑战。为探究此问题，我们访谈了四位UX从业者，了解他们在沟通中遇到的挑战及应对策略。我们的研究发现，提供示例用户流程——即代表语义任务的屏幕序列——作为证据能够强化沟通效果，但寻找相关示例仍具挑战性。为解决此问题，我们提出一种利用语义嵌入系统检索用户流程的方法。具体而言，我们设计了一个模型，该模型通过对比学习将屏幕的视觉特征与用户流程描述进行关联学习。一项调查证实，我们的方法检索出的用户流程更符合人类对相关性的感知。我们对结果进行了分析，并讨论了用户流程计算表征的意义。