Spatial embedding
Alberto Belussi, Sara Migliorini, Ahmed Eldawy · Proceedings of the 30th International Conference on Advances in Geographic Information Systems · 2022
Machine learning and deep learning techniques are increasingly applied to produce efficient query optimizers, in particular in regards to big data systems. The optimization of spatial operations is even more challenging due to the inherent complexity of such kind of operations, like spatial join, range queries, and the peculiarities of spatial data. Even though a few ML-based spatial query optimizers have been proposed in literature, their design limits their use, since each one is tailored for a specific collection of datasets, a specific operation, or specific a hardware. Changes to any of these will require building and training a completely new model which entails collecting a new very large training data to obtain a good model