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» Unsupervised Outlier Detection in Time Series Data
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ICDE
2006
IEEE
169views Database» more  ICDE 2006»
10 years 8 months ago
Unsupervised Outlier Detection in Time Series Data
Fraud detection is of great importance to financial institutions. This paper is concerned with the problem of finding outliers in time series financial data using Peer Group Analy...
Zakia Ferdousi, Akira Maeda
ADBIS
2006
Springer
200views Database» more  ADBIS 2006»
10 years 8 months ago
Anomaly Detection Using Unsupervised Profiling Method in Time Series Data
The anomaly detection problem has important applications in the field of fraud detection, network robustness analysis and intrusion detection. This paper is concerned with the prob...
Zakia Ferdousi, Akira Maeda
ICONIP
2004
10 years 4 months ago
Outliers Treatment in Support Vector Regression for Financial Time Series Prediction
Recently, the Support Vector Regression (SVR) has been applied in the financial time series prediction. The financial data are usually highly noisy and contain outliers. Detecting ...
Haiqin Yang, Kaizhu Huang, Laiwan Chan, Irwin King...
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
11 years 4 months ago
SPOT: A System for Detecting Projected Outliers From High-dimensional Data Streams
In this paper, we present a new technique, called Stream Projected Ouliter deTector (SPOT), to deal with outlier detection problem in high-dimensional data streams. SPOT is unique ...
Ji Zhang, Qigang Gao, Hai H. Wang
BMCBI
2005
120views more  BMCBI 2005»
10 years 2 months ago
Robust detection of periodic time series measured from biological systems
Background: Periodic phenomena are widespread in biology. The problem of finding periodicity in biological time series can be viewed as a multiple hypothesis testing of the spectr...
Miika Ahdesmäki, Harri Lähdesmäki, ...
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