Exploring a High-quality Outlying Feature Value Set for Noise-Resilient Outlier Detection in Categorical Data.
Hongzuo Xu|Yongjun Wang|Li Cheng|Yijie Wang|Xingkong Ma
| Anthology ID: | DBLP:conf/cikm/XuWCWM18 |
|---|---|
| Volume: | Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018 |
| Year: | 2018 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 17-26 |
| URL: | https://doi.org/10.1145/3269206.3271721 |
| DOI: | https://doi.org/10.1145/3269206.3271721 |
| DBLP: | conf/cikm/XuWCWM18 |
| BibTeX: |
@inproceedings{xu-2018-exploring,
author = {Hongzuo Xu and
Yongjun Wang and
Li Cheng and
Yijie Wang and
Xingkong Ma},
editor = {Alfredo Cuzzocrea and
James Allan and
Norman W. Paton and
Divesh Srivastava and
Rakesh Agrawal and
Andrei Z. Broder and
Mohammed J. Zaki and
K. Sel\c{c}uk Candan and
Alexandros Labrinidis and
Assaf Schuster and
Haixun Wang},
title = {{Exploring a High-quality Outlying Feature Value Set for Noise-Resilient Outlier Detection in Categorical Data}},
booktitle = {{Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018}},
pages = {17--26},
publisher = {ACM},
year = {2018},
url = {https://doi.org/10.1145/3269206.3271721},
doi = {https://doi.org/10.1145/3269206.3271721}
}