Probabilistic Maximum Range-Sum Queries on Spatial Database-Reference-Cited by-同舟云学术

Probabilistic Maximum Range-Sum Queries on Spatial Database

Published:2019-11-05 Issue: Volume: Page:
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Container-title:Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Author:

Liu Qiyu¹,Lian Xiang²,Chen Lei¹

Affiliation:

1. HKUST, Hong Kong SAR

2. Kent State University, Kent, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3347146.3359376

Reference32 articles.

1. 2019. Waze. https://www.waze.com/. 2019. Waze. https://www.waze.com/.

2. Rakesh Agrawal and Ramakrishnan Srikant. 1994. Fast Algorithms for Mining Association Rules in Large Databases. In VLDB. Morgan Kaufmann 487--499. Rakesh Agrawal and Ramakrishnan Srikant. 1994. Fast Algorithms for Mining Association Rules in Large Databases. In VLDB. Morgan Kaufmann 487--499.

3. Daichi Amagata and Takahiro Hara. 2016. Monitoring MaxRS in Spatial Data Streams. In EDBT. OpenProceedings.org 317--328. Daichi Amagata and Takahiro Hara. 2016. Monitoring MaxRS in Spatial Data Streams. In EDBT. OpenProceedings.org 317--328.

4. A General Framework for MaxRS and MaxCRS Monitoring in Spatial Data Streams

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