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GEO-BLEU: Similarity Measure for Geospatial Sequences
In recent geospatial research, the importance of modeling large-scale human mobility data and predicting trajectories is rising, in parallel with progress in text generation using large-scale corpora in natural language processing.
Learning Fine Grained Place Embeddings with Spatial Hierarchy from Human Mobility Trajectories
Place embeddings generated from human mobility trajectories have become a popular method to understand the functionality of places.
City2City: Translating Place Representations across Cities
Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges.
Pretraining Sentiment Classifiers with Unlabeled Dialog Data
Recent studies showed that pretraining with unlabeled data via a language model can improve the performance of classification models.
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