Author:
Angiulli Fabrizio,Basta Stefano,Lodi Stefano,Sartori Claudio
Publisher
Springer Berlin Heidelberg
Reference14 articles.
1. Angiulli, F., Basta, S., Pizzuti, C.: Distance-based detection and prediction of outliers. TKDE 18(2), 145–160 (2006)
2. Angiulli, F., Fassetti, F.: Dolphin: An efficient algorithm for mining distance-based outliers in very large datasets. TKDD 3(1) (2009)
3. Angiulli, F., Pizzuti, C.: Outlier mining in large high-dimensional data sets. TKDE 2(17), 203–215 (2005)
4. Asuncion, A., Newman, D.: UCI machine learning repository (2007)
5. Bay, S.D., Schwabacher, M.: Mining distance-based outliers in near linear time with randomization and a simple pruning rule. In: Proc. KDD (2003)
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. TOD;Proceedings of the VLDB Endowment;2022-11
2. Sparx: Distributed Outlier Detection at Scale;Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2022-08-14
3. GP-ELM-RNN: Garson-pruned extreme learning machine based replicator neural network for anomaly detection;Journal of King Saud University - Computer and Information Sciences;2019-09
4. GPU Strategies for Distance-Based Outlier Detection;IEEE Transactions on Parallel and Distributed Systems;2016-11-01
5. Miner*: A Weighted Distance Sum based Outlier Mining System of Star Spectrum Data;International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems;2016-10