| _version_ | 1866901542846595072 |
|---|---|
| author | anonymous |
| author_facet | anonymous |
| contents | <p>To systematically investigate the impact of spatial encoding granularity on model performance, we conduct a sensitivity analysis across multiple geohash levels. By integrating geohash representations of varying resolutions into a BERT-based framework, this experiment evaluates how different geohash fusion strategies influence POI-based urban land use classification. Specifically, geohash levels 5, 6, and 7 are adopted to capture spatial context from coarse to fine scales, enabling a comprehensive assessment of the role of spatial detail in enhancing semantic understanding and classification accuracy.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19562732 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Sensitivity Analysis of Multi-Level Geohash Fusion in BERT for POI-Based Urban Land Use Classification anonymous <p>To systematically investigate the impact of spatial encoding granularity on model performance, we conduct a sensitivity analysis across multiple geohash levels. By integrating geohash representations of varying resolutions into a BERT-based framework, this experiment evaluates how different geohash fusion strategies influence POI-based urban land use classification. Specifically, geohash levels 5, 6, and 7 are adopted to capture spatial context from coarse to fine scales, enabling a comprehensive assessment of the role of spatial detail in enhancing semantic understanding and classification accuracy.</p> |
| title | Sensitivity Analysis of Multi-Level Geohash Fusion in BERT for POI-Based Urban Land Use Classification |
| url | https://doi.org/10.5281/zenodo.19562732 |