Approximate Triangle Count and Clustering Coefficient
Summary: Approximate triangle count and clustering coefficient for graphs. Presents scalable estimation methods to compute these metrics efficiently on large graphs, bridging graph analytics and data-management concerns. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Siddharth Bhatia (Birla Institute of Technology and Science, Pilani)
BibTeX Citation
@inproceedings{bhatia_sigmod18,
title = {{Approximate Triangle Count and Clustering Coefficient}},
author = {Bhatia, Siddharth},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3183715},
url = {https://dl.acm.org/doi/10.1145/3183713.3183715},
year = {2018}
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