Scalable Evaluation of Local K-Function for Radius-Accurate Hotspot Detection in Spatial Networks-Reference-Cited by-同舟云学术

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Scalable Evaluation of Local K-Function for Radius-Accurate Hotspot Detection in Spatial Networks

Published:2023-11-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems
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Author:

Liu Yongyi¹^ORCID,Kang Yunfan¹^ORCID,Mahmood Ahmed²^ORCID,Magdy Amr¹^ORCID

Affiliation:

1. University of California - Riverside, Riverside, United States

2. Google LLC., Madison, United States

Funder

National Science Foundation, USA

Google

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589132.3625646

Reference41 articles.

1. Environmental Criminology

2. Identifying local spatial association in flow data

3. SWS

4. T. N. Chan , Z. Li , L. H. U, J. Xu , and R. Cheng . Fast Augmentation Algorithms for Network Kernel Density Visualization. Proceedings of the VLDB Endowment , 14 ( 9 ): 1503 -- 1516 , 2021 . T. N. Chan, Z. Li, L. H. U, J. Xu, and R. Cheng. Fast Augmentation Algorithms for Network Kernel Density Visualization. Proceedings of the VLDB Endowment, 14(9):1503--1516, 2021.

5. Fast network k-function-based spatial analysis

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