Map-graph interaction model for enhancing semantic exploration of urban road networks

doi:10.13474/j.cnki.11-2246.2026.0617

Abstract

Abstract: [Purposes] To address the inadequacies in expressing urban road semantics and the disconnect between spatial and semantic information in online maps,we propose a map-graph interaction model to enhance semantic exploration and cognitive reasoning capabilities.[Methods]By establishing a bidirectional mapping mechanism between geometric space and semantic space,we construct a map-graph interaction model.Integrating large language models,we build a natural language question-answering interface to achieve closed-loop “spatial-semantic” interaction.[Findings] The prototype system effectively implements bidirectional interaction between spatial and semantic elements,enabling natural language-based road knowledge queries and visualization.[Conclusions] This model effectively bridges the gap between road spatial representation and road semantic knowledge.It not only enhances the efficiency of road information transmission but also lowers the cognitive threshold for understanding complex road semantics through natural language interaction,providing robust support for future urban planning and spatial intelligence decision-making.

Key words: web map, urban road semantics, knowledge graph, bidirectional interaction

CLC Number:

P208

YIN Zhangcai, ZHANG Zheng, CHEN Yiran. Map-graph interaction model for enhancing semantic exploration of urban road networks[J]. Bulletin of Surveying and Mapping, 2026, 0(6): 112-118.

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URL: http://tb.chinasmp.com/EN/10.13474/j.cnki.11-2246.2026.0617

http://tb.chinasmp.com/EN/Y2026/V0/I6/112

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