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- W3217005823 abstract "An organized knowledge base can facilitate the exploration of existing knowledge and the detection of emerging topics in a domain. Knowledge about and around Geographic Information Science and its associated system technologies (GIS) is complex, extensive and emerging rapidly. Taking the challenge, we built a GIS knowledge graph (GIS-KG) by (1) merging existing GIS bodies of knowledge to create a hierarchical ontology and then (2) applying deep-learning methods to map GIS publications to the ontology. We conducted several experiments on information retrieval to evaluate the novelty and effectiveness of the GIS-KG. Results showed the robust support of GIS-KG for knowledge search of existing GIS topics and potential to explore emerging research themes." @default.
- W3217005823 created "2021-12-06" @default.
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- W3217005823 date "2021-11-26" @default.
- W3217005823 modified "2023-10-14" @default.
- W3217005823 title "GIS-KG: building a large-scale hierarchical knowledge graph for geographic information science" @default.
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- W3217005823 doi "https://doi.org/10.1080/13658816.2021.2005795" @default.
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