CG-GNN: A Novel Compiled Graphs-based Feature Extraction Method for Enterprise Social Networks.
Tatsuya Konishi|Shuichiro Haruta|Mori Kurokawa|Kenta Tsukatsune|Yuto Mizutani|Tomoaki Saito|Hideki Asoh|Chihiro Ono
| Anthology ID: | DBLP:conf/icdar2/KonishiHKTMSAO23 |
|---|---|
| Volume: | Proceedings of the 4th ACM Workshop on Intelligent Cross-Data Analysis and Retrieval, ICDAR 2023, Thessaloniki, Greece, June 12-15, 2023 |
| Year: | 2023 |
| Venue: | ACM Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR) |
| Publisher: | ACM |
| Pages: | 24-31 |
| URL: | https://doi.org/10.1145/3592571.3592976 |
| DOI: | https://doi.org/10.1145/3592571.3592976 |
| DBLP: | conf/icdar2/KonishiHKTMSAO23 |
| BibTeX: |
@inproceedings{konishi-2023-cggnn,
author = {Tatsuya Konishi and
Shuichiro Haruta and
Mori Kurokawa and
Kenta Tsukatsune and
Yuto Mizutani and
Tomoaki Saito and
Hideki Asoh and
Chihiro Ono},
editor = {Guillaume Habault and
Minh-Son Dao and
Michael Riegler and
Duc-Tien Dang-Nguyen and
Yuta Nakashima and
Cathal Gurrin},
title = {{CG-GNN: A Novel Compiled Graphs-based Feature Extraction Method for Enterprise Social Networks}},
booktitle = {{Proceedings of the 4th ACM Workshop on Intelligent Cross-Data Analysis and Retrieval, ICDAR 2023, Thessaloniki, Greece, June 12-15, 2023}},
pages = {24--31},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3592571.3592976},
doi = {https://doi.org/10.1145/3592571.3592976}
}