In recent years, the quantity of unstructured information sources, such as documents that include complex information about climate change has grown exponentially. Machine learning techniques may be used to extract semantic information from these unstructured sources to enable se...
Open access
Research Article10.9734/ijecc/2024/v14i84361
Recent advances in geospatial artificial intelligence (GeoAI) have highlighted the potential of combining natural language processing (NLP) and graph-based learning for extracting semantically enriched spatial knowledge. This study describes the development of a lightweight hybri...
Open access
Research Article10.9734/jgeesi/2026/v30i11001
Extracting entity connectivity from texts is important for uncovering how places relate within real-world discourse. While structured data is informative, textual data captures rich contextual and semantic knowledge, enabling us to identify hidden networks of interdependence and...
Open access
Research Article10.9734/jgeesi/2026/v30i1999