Efficient Attribute (α, Β)-Core Detection in Large Bipartite Graphs (Student Abstract)

Yanping Wu, Renjie Sun, Chen Chen, Xiaoyang Wang

AAAI 2022 pp. 13087-13088

doi:10.1609/AAAI.V36I11.21680 /aaai/2022/wu2022aaai-efficient/

Abstract

In this paper, we propose a novel problem, named rational (alpha, beta)-core detection in attribute bipartite graphs (RCD-ABG), which retrieves the connected (alpha, beta)-core with the largest rational score. A basic greedy framework with an optimized strategy is developed and extensive experiments are conducted to evaluate the performance of the techniques.

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Cite

Text

Wu et al. "Efficient Attribute (α, Β)-Core Detection in Large Bipartite Graphs (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21680

Markdown

[Wu et al. "Efficient Attribute (α, Β)-Core Detection in Large Bipartite Graphs (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/wu2022aaai-efficient/) doi:10.1609/AAAI.V36I11.21680

BibTeX

@inproceedings{wu2022aaai-efficient,
  title     = {{Efficient Attribute (α, Β)-Core Detection in Large Bipartite Graphs (Student Abstract)}},
  author    = {Wu, Yanping and Sun, Renjie and Chen, Chen and Wang, Xiaoyang},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {13087-13088},
  doi       = {10.1609/AAAI.V36I11.21680},
  url       = {https://mlanthology.org/aaai/2022/wu2022aaai-efficient/}
}