Urban region representation is essential for various applications such as urban planning, resource allocation, and policy development. Traditional methods rely on fixed, predefined region boundaries, which fail to capture the dynamic and complex nature of real-world urban areas. In this paper, we propose the Boundary Prompting Urban Region Representation Framework (BPURF), a novel approach that allows for elastic urban region definitions. BPURF comprises two key components: (1) A spatial token dictionary, where urban entities are treated as tokens and integrated into a unified token graph, and (2) a region token set representation model which utilize token aggregation and a multi-channel model to embed token sets corresponding to region boundaries. Additionally, we propose fast token set extraction strategy to enable online token set extraction during training and prompting. This framework enables the definition of urban regions through boundary prompting, supporting varying region boundaries and adapting to different tasks. Extensive experiments demonstrate the effectiveness of BPURF in capturing the complex characteristics of urban regions.

本研究解决了传统城市区域表示方法无法适应动态复杂城市特征的问题，提出了边界提示城市区域表示框架（BPURF），通过将城市实体视为令牌，构建统一的令牌图，从而实现了灵活的城市区域定义。实验结果表明，BPURF在捕捉城市区域的复杂特性方面表现出色，具有广泛的应用潜力。

边界提示：通过基于图的空间分词实现弹性城市区域表示