SGES: A General and Space-efficient Framework for Graphlet Counting in Graph Streams.
Chen Yang|Lailong Luo|Yuliang Lu|Chu Huang|Qianzhen Zhang|Guozheng Yang|Deke Guo
| Anthology ID: | DBLP:conf/cikm/YangLLHZYG24 |
|---|---|
| Volume: | Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024 |
| Year: | 2024 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 2817-2826 |
| URL: | https://doi.org/10.1145/3627673.3679739 |
| DOI: | https://doi.org/10.1145/3627673.3679739 |
| DBLP: | conf/cikm/YangLLHZYG24 |
| BibTeX: |
@inproceedings{yang-2024-sges,
author = {Chen Yang and
Lailong Luo and
Yuliang Lu and
Chu Huang and
Qianzhen Zhang and
Guozheng Yang and
Deke Guo},
editor = {Edoardo Serra and
Francesca Spezzano},
title = {{SGES: A General and Space-efficient Framework for Graphlet Counting in Graph Streams}},
booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}},
pages = {2817--2826},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3627673.3679739},
doi = {https://doi.org/10.1145/3627673.3679739}
}