Efficient Estimation of Triangles in Very Large Graphs
Author:
Affiliation:
1. University of Windsor, Windsor, ON, Canada
Funder
NSERC
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2983323.2983849
Reference29 articles.
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3. The webgraph framework I
4. Counting triangles in data streams
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1. Efficient Sampling Algorithms for Approximate Temporal Motif Counting;Proceedings of the 29th ACM International Conference on Information & Knowledge Management;2020-10-19
2. How to Count Triangles, without Seeing the Whole Graph;Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining;2020-08-20
3. Temporal locality-aware sampling for accurate triangle counting in real graph streams;The VLDB Journal;2020-08-12
4. Retrieving Top Weighted Triangles in Graphs;Proceedings of the 13th International Conference on Web Search and Data Mining;2020-01-20
5. Revisiting Wedge Sampling for Triangle Counting;The World Wide Web Conference on - WWW '19;2019
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