Maximum Biclique Search at Billion Scale
Summary: Divides max-biclique search into O(log n) subproblems with restricted regions; prunes by one-hop/two-hop neighbors while preserving the optimal constrained biclique. Demonstrates billion-scale graphs and a 50% recall gain on Alibaba fraud detection. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bingqing Lyu
- 2. Lu Qin
- 3. Xuemin Lin
- 4. Ying Zhang
- 5. Zhengping Qian
- 6. Jingren Zhou
Incoming Citations (Sorted by Pagerank)
Showing 26 of 26 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 847 | Finding the Maximum Clique in Massive Graphs | 2017 | VLDB | 0.00015993322 |
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| 847 | Finding the Maximum Clique in Massive Graphs | 2017 | VLDB | 0.00015993322 |
| 7,757 | Identifying Similar-Bicliques in Bipartite Graphs | 2022 | VLDB | 4.6598957e-05 |
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| 10,119 | Theoretically and Practically Efficient Maximum Biclique Search | 2026 | SIGMOD | 4.1945683e-05 |