Density-friendly Graph Decomposition-Reference-Cited by-同舟云学术

Density-friendly Graph Decomposition

Published:2015-05-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 24th International Conference on World Wide Web
language:
Short-container-title:

Author:

Tatti Nikolaj¹,Gionis Aristides¹

Affiliation:

1. Aalto University, Espoo, Finland

Publisher

International World Wide Web Conferences Steering Committee

Link

https://dl.acm.org/doi/pdf/10.1145/2736277.2741119

Reference29 articles.

1. A. Agresti. Analysis of Ordinal Categorical Data. John Wiley & Sons 2nd edition 2010. A. Agresti. Analysis of Ordinal Categorical Data. John Wiley & Sons 2nd edition 2010.

2. J. I. Alvarez-Hamelin L. Dall'Asta A. Barrat and A. Vespignani. k-core decomposition: a tool for the visualization of large scale networks. CoRR abs/cs/0504107 2005. J. I. Alvarez-Hamelin L. Dall'Asta A. Barrat and A. Vespignani. k-core decomposition: a tool for the visualization of large scale networks. CoRR abs/cs/0504107 2005.

3. An Empirical Distribution Function for Sampling with Incomplete Information

Cited by 48 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Counting-based Approach for Efficient k-Clique Densest Subgraph Discovery;Proceedings of the ACM on Management of Data;2024-05-29

2. Finding Subgraphs with Maximum Total Density and Limited Overlap in Weighted Hypergraphs;ACM Transactions on Knowledge Discovery from Data;2024-02-12

3. Accelerating directed densest subgraph queries with software and hardware approaches;The VLDB Journal;2023-07-31

4. Scaling Up k-Clique Densest Subgraph Detection;Proceedings of the ACM on Management of Data;2023-05-26

5. Scalable Algorithms for Densest Subgraph Discovery;2023 IEEE 39th International Conference on Data Engineering (ICDE);2023-04