Efficient Sampling Algorithms for Approximate Temporal Motif Counting
Author:
Affiliation:
1. Hunan University, Changsha, China
2. National University of Singapore, Singapore, Singapore
3. Singapore Management University & Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies, Singapore, Singapore
Funder
National Natural Science Foundation of China
the Singapore Ministry of Education
the China Scholarships Council
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3340531.3411862
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2. Counting Graphlets
3. Lorenzo De Stefani Alessandro Epasto Matteo Riondato and Eli Upfal. 2016. TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size. In KDD. 825--834. Lorenzo De Stefani Alessandro Epasto Matteo Riondato and Eli Upfal. 2016. TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size. In KDD. 825--834.
4. Roohollah Etemadi Jianguo Lu and Yung H. Tsin. 2016. Efficient Estimation of Triangles in Very Large Graphs. In CIKM. 1251--1260. Roohollah Etemadi Jianguo Lu and Yung H. Tsin. 2016. Efficient Estimation of Triangles in Very Large Graphs. In CIKM. 1251--1260.
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