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Learning dynamic relational heterogeneity for spatiotemporal prediction with geographical meta-knowledge.

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Title: Learning dynamic relational heterogeneity for spatiotemporal prediction with geographical meta-knowledge.
Authors: Chen, Kaiqi1, Tan, Xiaoyong1, bariomax@csu.edu.cn, Deng, Min1,2, Lei, Kaiyuan1, Yang, Wentao3, Liu, Huimin1,2, Huang, Cheng4,5
Source: International Journal of Geographical Information Science; Dec2025, Vol. 39 Issue 12, p2913-2942, 30p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 189213708
AccessLevel: 2
PubType: Academic Journal
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  Data: Learning dynamic relational heterogeneity for spatiotemporal prediction with geographical meta-knowledge.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Geographical+Information+Science%22">International Journal of Geographical Information Science</searchLink>; Dec2025, Vol. 39 Issue 12, p2913-2942, 30p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=189213708
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/13658816.2025.2506528
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      – Code: eng
        Text: English
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        PageCount: 30
        StartPage: 2913
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      – TitleFull: Learning dynamic relational heterogeneity for spatiotemporal prediction with geographical meta-knowledge.
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            NameFull: Tan, Xiaoyong
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            NameFull: Deng, Min
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            NameFull: Yang, Wentao
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            NameFull: Liu, Huimin
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            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
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