Conference Proceedings

USTAR: Online Multimodal Embedding for Modeling User-Guided Spatiotemporal Activity

Amila Silva, Shanika Karunasekera, Chris Leckie, Ling Luo

Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 | IEEE | Published : 2020


Building spatiotemporal activity models for people's activities in urban spaces is important for understanding the ever-increasing complexity of urban dynamics. With the emergence of Geo-Tagged Social Media (GTSM) records, previous studies demonstrate the potential of GTSM records for spatiotemporal activity modeling. State-of-the-art methods for this task embed different modalities (location, time, and text) of GTSM records into a single embedding space. However, they ignore Non-GeoTagged Social Media (NGTSM) records, which generally account for the majority of posts (e.g., more than 95% in Twitter), and could represent a great source of information to alleviate the sparsity of GTSM records..

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