Efficient and Effective Anchored Densest Subgraph Search: A Convex-programming based Approach-Reference-Cited by-同舟云学术

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Efficient and Effective Anchored Densest Subgraph Search: A Convex-programming based Approach

Published:2024-08-24 Issue: Volume:28 Page:3907-3918
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Ye Xiaowei¹^ORCID,Li Rong-Hua²^ORCID,Liang Lei³^ORCID,Liu Zhizhen³^ORCID,Lin Longlong⁴^ORCID,Wang Guoren¹^ORCID

Affiliation:

1. Beijing Institute of Technology, Beijing, China

2. Key Laboratory of Intelligent Supply Chain Technology, Longgang District, Shenzhen; Beijing Institute of Technology, Beijing, China

3. Ant Group, Hangzhou, China

4. Southwest University, Chongqing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671727

Reference50 articles.

1. 2017. Zachary karate club network dataset - KONECT. http://konect.cc/ networks/ucidata-zachary

2. Truss-based community search

3. Morteza Alamgir and Ulrike von Luxburg. 2010. Multi-agent Random Walks for Local Clustering on Graphs. In ICDM 2010. IEEE Computer Society, 18--27.

4. Aris Anagnostopoulos Luca Becchetti Adriano Fazzone Cristina Menghini and Chris Schwiegelshohn. 2020. Spectral Relaxations and Fair Densest Subgraphs. In CIKM. 35--44.

5. Reid Andersen and Kumar Chellapilla. 2009. Finding Dense Subgraphs with Size Bounds. In WAW, Vol. 5427. Springer, 25--37.

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