TY - GEN
T1 - Wadjet
T2 - 34th IEEE International Conference on Data Engineering, ICDE 2018
AU - Sadik, Shiblee
AU - Gruenwald, Le
AU - Leal, Eleazar
PY - 2018/10/24
Y1 - 2018/10/24
N2 - Data streams are sequences of data points that have the properties of transiency, infiniteness, concept drift, uncertainty, multi-dimensionality, cross-correlation among different streams, asynchronous arrival, and heterogeneity. In this paper we propose a new outlier detection technique for multiple multi-dimensional data streams, called Wadjet, that addresses all the issues of outlier detection in multiple data streams. Wadjet exploits the temporal correlations to identify outliers in each individual data stream, and after this, it exploits the cross-correlations between data streams to identify points that do not conform with these cross-correlations. Experiments comparing Wadjet against existing techniques on real and synthetic datasets show that Wadjet achieves 18.8X higher precision, and competitive execution time and recall.
AB - Data streams are sequences of data points that have the properties of transiency, infiniteness, concept drift, uncertainty, multi-dimensionality, cross-correlation among different streams, asynchronous arrival, and heterogeneity. In this paper we propose a new outlier detection technique for multiple multi-dimensional data streams, called Wadjet, that addresses all the issues of outlier detection in multiple data streams. Wadjet exploits the temporal correlations to identify outliers in each individual data stream, and after this, it exploits the cross-correlations between data streams to identify points that do not conform with these cross-correlations. Experiments comparing Wadjet against existing techniques on real and synthetic datasets show that Wadjet achieves 18.8X higher precision, and competitive execution time and recall.
KW - Data streams
KW - Heterogeneous data streams
KW - Outlier detection
KW - Uncertain data streams
UR - http://www.scopus.com/inward/record.url?scp=85057079088&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85057079088&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2018.00118
DO - 10.1109/ICDE.2018.00118
M3 - Conference contribution
AN - SCOPUS:85057079088
T3 - Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
SP - 1236
EP - 1239
BT - Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 April 2018 through 19 April 2018
ER -