Maximizing Multi-scale Spatial Statistical Discrepancy-Reference-Cited by-同舟云学术

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Maximizing Multi-scale Spatial Statistical Discrepancy

Published:2014-11-03 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
language:
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Author:

Dong Weishan¹,Yao Renjie²,Ma Chunyang¹,Li Changsheng¹,Shi Lei³,Wang Lu⁴,Wang Yu¹,Gao Peng¹,Yan Junchi⁵

Affiliation:

1. IBM Research - China, Beijing, China

2. IBM Research - China, Beijing & Northeastern University, Shenyang, China

3. SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China

4. University of Chinese Academy of Sciences, Beijing, China

5. IBM Research - China, Shanghai, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2661829.2662007

Reference18 articles.

1. Spatial scan statistics

2. Using AMOEBA to Create a Spatial Weights Matrix and Identify Spatial Clusters

3. A stack-based prospective spatio-temporal data analysis approach

4. Detect irregularly shaped spatio-temporal clusters for decision support

5. Detecting Irregularly Shaped Significant Spatial and Spatio-Temporal Clusters

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