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Non-IID spatio-temporal prediction in smart cities

Published: 07 April 2022 Publication History

Abstract

Non-IID spatio-temporal prediction research points toward emerging directions and fundamental solutions to address various complexities from the perspective of both data couplings and heterogeneity. Delving into the non-IID challenge and opportunity of spatio-temporal prediction in smart cities, this article also addresses current solutions to bring some inspiration to future researchers.

References

[1]
Zheng, Y. and Licia, C. et al. Urban computing: Concepts, methodologies, and applications. ACM Transactions on intelligent Systems and Technology 5, 3 (2014), 1--55.
[2]
Longbing, C. Non-IID recommender systems: A review and framework of recommendation paradigm shifting. Engineering 2, 2 (2016), 212--224.
[3]
Jian, S. and Pang, G. et al. Cure: Flexible categorical data representation by hierarchical coupling learning.] IEEE Transactions on Knowledge and Data Engineering 31, 5 (2018,), 853--866.
[4]
Ren, S. and Guo, B. et al. DeepExpress: Heterogeneous and coupled sequence modeling for express delivery prediction. arXiv preprint arXiv:2108.08170, 2021.

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Published In

cover image XRDS: Crossroads, The ACM Magazine for Students
XRDS: Crossroads, The ACM Magazine for Students  Volume 28, Issue 3
Smart Cities
Spring 2022
64 pages
ISSN:1528-4972
EISSN:1528-4980
DOI:10.1145/3530850
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 April 2022
Published in XRDS Volume 28, Issue 3

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