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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Learning Geo-Contextual Embeddings for Commuting Flow Prediction

February 1, 2023

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Authors

Zhicheng Liu

Southeast University


Fabio Miranda

New York University


Weiting Xiong

Southeast University


Junyan Yang

Southeast University


Qiao Wang

Southeast University


Claudio Silva

New York University


DOI:

10.1609/aaai.v34i01.5425


Abstract:

Predicting commuting flows based on infrastructure and land-use information is critical for urban planning and public policy development. However, it is a challenging task given the complex patterns of commuting flows. Conventional models, such as gravity model, are mainly derived from physics principles and limited by their predictive power in real-world scenarios where many factors need to be considered. Meanwhile, most existing machine learning-based methods ignore the spatial correlations and fail to model the influence of nearby regions. To address these issues, we propose Geo-contextual Multitask Embedding Learner (GMEL), a model that captures the spatial correlations from geographic contextual information for commuting flow prediction. Specifically, we first construct a geo-adjacency network containing the geographic contextual information. Then, an attention mechanism is proposed based on the framework of graph attention network (GAT) to capture the spatial correlations and encode geographic contextual information to embedding space. Two separate GATs are used to model supply and demand characteristics. To enhance the effectiveness of the embedding representation, a multitask learning framework is used to introduce stronger restrictions, forcing the embeddings to encapsulate effective representation for flow prediction. Finally, a gradient boosting machine is trained based on the learned embeddings to predict commuting flows. We evaluate our model using real-world dataset from New York City and the experimental results demonstrate the effectiveness of our proposed method against the state of the art.

Topics: AAAI

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HOW TO CITE:

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva Learning Geo-Contextual Embeddings for Commuting Flow Prediction Proceedings of the AAAI Conference on Artificial Intelligence (2020) 808-816.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva Learning Geo-Contextual Embeddings for Commuting Flow Prediction AAAI 2020, 808-816.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva (2020). Learning Geo-Contextual Embeddings for Commuting Flow Prediction. Proceedings of the AAAI Conference on Artificial Intelligence, 808-816.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva. Learning Geo-Contextual Embeddings for Commuting Flow Prediction. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.808-816.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva. 2020. Learning Geo-Contextual Embeddings for Commuting Flow Prediction. "Proceedings of the AAAI Conference on Artificial Intelligence". 808-816.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva. (2020) "Learning Geo-Contextual Embeddings for Commuting Flow Prediction", Proceedings of the AAAI Conference on Artificial Intelligence, p.808-816

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva, "Learning Geo-Contextual Embeddings for Commuting Flow Prediction", AAAI, p.808-816, 2020.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva. "Learning Geo-Contextual Embeddings for Commuting Flow Prediction". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.808-816.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva. "Learning Geo-Contextual Embeddings for Commuting Flow Prediction". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 808-816.

Zhicheng Liu||Fabio Miranda||Weiting Xiong||Junyan Yang||Qiao Wang||Claudio Silva. Learning Geo-Contextual Embeddings for Commuting Flow Prediction. AAAI[Internet]. 2020[cited 2023]; 808-816.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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