TY - CHAP
T1 - Fast memory efficient local outlier detection in data streams (extended abstract)
AU - Salehi, Mahsa
AU - Leckie, Christopher
AU - Bezdek, James C.
AU - Vaithianathan, Tharshan
AU - Zhang, Xuyun
PY - 2017
Y1 - 2017
N2 - Outlier detection is an important task in data mining. With the growing need to analyze high speed data streams, the task of outlier detection becomes even more challenging as traditional outlier detection techniques can no longer assume that all the data can be stored for processing. While the well-known Local Outlier Factor (LOF) algorithm has an incremental version (called iLOF), it assumes unbounded memory to keep all previous data points. In this paper, we propose a memory efficient incremental local outlier (MiLOF) detection algorithm for data streams, and a more flexible version (MiLOF_F), both have an accuracy close to iLOF but within a fixed memory bound. In addition MiLOF_F is robust to changes in the number of data points, underlying clusters and dimensions in the data stream.
AB - Outlier detection is an important task in data mining. With the growing need to analyze high speed data streams, the task of outlier detection becomes even more challenging as traditional outlier detection techniques can no longer assume that all the data can be stored for processing. While the well-known Local Outlier Factor (LOF) algorithm has an incremental version (called iLOF), it assumes unbounded memory to keep all previous data points. In this paper, we propose a memory efficient incremental local outlier (MiLOF) detection algorithm for data streams, and a more flexible version (MiLOF_F), both have an accuracy close to iLOF but within a fixed memory bound. In addition MiLOF_F is robust to changes in the number of data points, underlying clusters and dimensions in the data stream.
UR - http://www.scopus.com/inward/record.url?scp=85021238905&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2017.32
DO - 10.1109/ICDE.2017.32
M3 - Conference abstract
T3 - IEEE International Conference on Data Engineering
SP - 51
EP - 52
BT - 2017 IEEE 33rd International Conference on Data Engineering (ICDE 2017)
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - Los Alamitos, CA
T2 - IEEE 33rd International Conference on Data Engineering (ICDE)
Y2 - 19 April 2017 through 22 April 2017
ER -