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We propose a general framework for multi-source spatio-temporal data analysis via knowledge graph embedding.
A general framework that extracts low-dimensional feature representation from multi-source spatio-temporal data in a high-dimensional space, and recognizes ...
To explore the network structure and semantic relationships, we propose a general framework for multi-source spatio-temporal data analysis via knowledge graph ...
Abstract: Multi-source spatio-temporal data analysis is an important task in the development of smart cities. However, traditional data analysis methods ...
Many knowledge graphs (KG) contain spatial and temporal information. Most KG embedding models follow triple-based representation and often neglect the ...
Urban Multi-Source Spatio-Temporal Data Analysis Aware Knowledge Graph Embedding. L. Zhao, H. Deng, L. Qiu, S. Li, Z. Hou, H. Sun, and Y. Chen.
Urban Multi-Source Spatio-Temporal Data Analysis Aware Knowledge Graph Embedding. Symmetry 2020, 12, 199. https://doi.org/10.3390/sym12020199. AMA Style. Zhao ...
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This paper presents UUKG, the unified urban knowledge graph dataset for knowledge-enhanced urban spatiotemporal predictions.
Dec 30, 2021 · In this paper, we focus on modeling users' spatio-temporal mobility patterns based on knowledge graph techniques, and predicting users' future ...
Urban multi-source spatio-temporal data analysis aware knowledge graph embedding (Symmetry 2020) [paper]. Others. Citation trajectory prediction via ...