Solving the Sparsity Problem in Recommendations via Cross-Domain Item Embedding Based on Co-Clustering.
Yaqing Wang|Chunyan Feng|Caili Guo|Yunfei Chu|Jenq-Neng Hwang
| Anthology ID: | DBLP:conf/wsdm/WangFGCH19 |
|---|---|
| Volume: | Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, VIC, Australia, February 11-15, 2019 |
| Year: | 2019 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 717-725 |
| URL: | https://doi.org/10.1145/3289600.3290973 |
| DOI: | https://doi.org/10.1145/3289600.3290973 |
| DBLP: | conf/wsdm/WangFGCH19 |
| BibTeX: |
@inproceedings{wang-2019-solving,
author = {Yaqing Wang and
Chunyan Feng and
Caili Guo and
Yunfei Chu and
Jenq-Neng Hwang},
editor = {J. Shane Culpepper and
Alistair Moffat and
Paul N. Bennett and
Kristina Lerman},
title = {{Solving the Sparsity Problem in Recommendations via Cross-Domain Item Embedding Based on Co-Clustering}},
booktitle = {{Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, VIC, Australia, February 11-15, 2019}},
pages = {717--725},
publisher = {ACM},
year = {2019},
url = {https://doi.org/10.1145/3289600.3290973},
doi = {https://doi.org/10.1145/3289600.3290973}
}