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» Unsupervised Outlier Detection in Time Series Data
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MLDM
2007
Springer
13 years 11 months ago
Outlier Detection with Kernel Density Functions
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detec...
Longin Jan Latecki, Aleksandar Lazarevic, Dragolju...
SDM
2010
SIAM
156views Data Mining» more  SDM 2010»
13 years 6 months ago
Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Alireza Vahdatpour, Majid Sarrafzadeh
ICDE
2009
IEEE
125views Database» more  ICDE 2009»
14 years 7 months ago
Temporal Outlier Detection in Vehicle Traffic Data
Outlier detection in vehicle traffic data is a practical problem that has gained traction lately due to an increasing capability to track moving vehicles in city roads. In contrast...
Xiaolei Li, Zhenhui Li, Jiawei Han, Jae-Gil Lee
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
11 years 7 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
ICDM
2002
IEEE
130views Data Mining» more  ICDM 2002»
13 years 10 months ago
Unsupervised Segmentation of Categorical Time Series into Episodes
This paper describes an unsupervised algorithm for segmenting categorical time series into episodes. The VOTING-EXPERTS algorithm first collects statistics about the frequency an...
Paul R. Cohen, Brent Heeringa, Niall M. Adams