Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation.
Ke Tu|Peng Cui|Daixin Wang|Zhiqiang Zhang|Jun Zhou|Yuan Qi|Wenwu Zhu
| Anthology ID: | DBLP:conf/cikm/TuCWZZ0021 |
|---|---|
| Volume: | CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021 |
| Year: | 2021 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 1834-1843 |
| URL: | https://doi.org/10.1145/3459637.3482331 |
| DOI: | https://doi.org/10.1145/3459637.3482331 |
| DBLP: | conf/cikm/TuCWZZ0021 |
| BibTeX: |
@inproceedings{tu-2021-conditional,
author = {Ke Tu and
Peng Cui and
Daixin Wang and
Zhiqiang Zhang and
Jun Zhou and
Yuan Qi and
Wenwu Zhu},
editor = {Gianluca Demartini and
Guido Zuccon and
J. Shane Culpepper and
Zi Huang and
Hanghang Tong},
title = {{Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation}},
booktitle = {{CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021}},
pages = {1834--1843},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3459637.3482331},
doi = {https://doi.org/10.1145/3459637.3482331}
}