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Spatial Language Representation with Multi-Level Geocoding
[article]
2020
arXiv
pre-print
We present a multi-level geocoding model (MLG) that learns to associate texts to geographic locations. The Earth's surface is represented using space-filling curves that decompose the sphere into a hierarchy of similarly sized, non-overlapping cells. MLG balances generalization and accuracy by combining losses across multiple levels and predicting cells at each level simultaneously. Without using any dataset-specific tuning, we show that MLG obtains state-of-the-art results for toponym
arXiv:2008.09236v1
fatcat:ahsbiqnjjbcr5haqngo7t7xzau