Efficient Estimation of Heat Kernel PageRank for Local Clustering
Summary: TEA and TEA+: HKPR-based local clustering with relative-error guarantees and near-linear time in cluster size, via deterministic rough HKPR and Monte Carlo refinement. TEA+ beats prior methods ~4x on real graphs (Twitter, Friendster), enabling scalable clustering on billion-edge networks. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Renchi Yang (Nanyang Technological University)
- 2. Xiaokui Xiao (National University of Singapore)
- 3. Zhewei Wei (Renmin University of China)
- 4. Sourav S Bhowmick (Nanyang Technological University)
- 5. Jun Zhao (Nanyang Technological University)
- 6. Rong-Hua Li (Beijing Institute of Technology)
BibTeX Citation
@inproceedings{yang_sigmod19,
title = {{Efficient Estimation of Heat Kernel PageRank for Local Clustering}},
author = {Yang, Renchi and Xiao, Xiaokui and Wei, Zhewei and Bhowmick, Sourav S and Zhao, Jun and Li, Rong-Hua},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3319886},
url = {https://dl.acm.org/doi/10.1145/3299869.3319886},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,225 | HubPPR: Effective Indexing for Approximate Personalized PageRank | 2017 | VLDB | 8.9183159e-05 |
| 2,580 | Community Detection in Social Networks: An In-depth Benchmarking Study with a Procedure-Oriented Framework | 2015 | VLDB | 8.3887788e-05 |
| 3,616 | Parallel Local Graph Clustering | 2016 | VLDB | 7.2559471e-05 |
| 4,024 | TopPPR: Top-k Personalized PageRank Queries with Precision Guarantees on Large Graphs | 2018 | SIGMOD | 6.9479974e-05 |
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