用动态城市图嵌入预测中国经济活力，借鉴相似城市的发展轨迹。
Tracing Footsteps of Similar Cities: Modeling Urban Economic Vitality with Dynamic Inter-City Graph Embeddings
- 构建多图框架融合产业、人口、迁移等15年动态关系。
- 在2005-2021年中国城市数据上，预测创业与就业更准确。
- 适合城市规划者和政策制定者参考，开源可复用。
城市经济活力是衡量城市长期增长潜力的关键指标，包括年新增企业数和就业人口等。本文提出ECO-GROW，一种基于中国城市间网络（2005–2021）的多图框架，生成刻画经济活力的城市嵌入。传统方法依赖静态城市聚合数据，难以捕捉“今日某城市的发展轨迹，可能预示其结构相似城市未来的演变”这一动态规律。ECO-GROW通过整合产业关联、兴趣点相似性、人口迁移相似性及15年时间演化，结合动态Top-K GCN自适应选择关键城市连接，以及自适应图评分机制动态加权跨区域影响。模型还引入基于Barabasi近似的链接预测任务以优化图表示。实验表明，该模型在预测创业活动与就业趋势方面优于传统模型。代码已开源，供政府与公共机构用于数据驱动的城市规划、经济政策制定与资源配置决策。
原文摘要 · Abstract (English)
Urban economic vitality is a crucial indicator of a city's long-term growth potential, comprising key metrics such as the annual number of new companies and the population employed. However, modeling urban economic vitality remains challenging. This study develops ECO-GROW, a multi-graph framework modeling China's inter-city networks (2005-2021) to generate urban embeddings that model urban economic vitality. Traditional approaches relying on static city-level aggregates fail to capture a fundamental dynamic: the developmental trajectory of one city today may mirror that of its structurally similar counterparts tomorrow. ECO-GROW overcomes this limitation by integrating industrial linkages, POI similarities, migration similarities and temporal network evolution over 15 years. The framework combines a Dynamic Top-K GCN to adaptively select influential inter-city connections and an adaptive Graph Scorer mechanism to dynamically weight cross-regional impacts. Additionally, the model incorporates a link prediction task based on Barabasi Proximity, optimizing the graph representation. Experimental results demonstrate ECO-GROW's superior accuracy in predicting entrepreneurial activities and employment trends compared to conventional models. By open-sourcing our code, we enable government agencies and public sector organizations to leverage big data analytics for evidence-based urban planning, economic policy formulation, and resource allocation decisions that benefit society at large.
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