Sciweavers

GI
2004
Springer
13 years 10 months ago
Outlier Detection by Rareness Assumption
: A concept for identification of candidates for outliers is presented, with a focus on nominal variables. The database concerned is searched for rules that are almost universally...
Tomas Hrycej, Jochen Hipp
KDD
2005
ACM
205views Data Mining» more  KDD 2005»
13 years 10 months ago
Feature bagging for outlier detection
Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
Aleksandar Lazarevic, Vipin Kumar
CLEANDB
2006
ACM
185views Database» more  CLEANDB 2006»
13 years 10 months ago
In-network Outlier Cleaning for Data Collection in Sensor Networks
Outliers are very common in the environmental data monitored by a sensor network consisting of many inexpensive, low fidelity, and frequently failed sensors. The limited battery ...
Yongzhen Zhuang, Lei Chen 0002
ICDM
2006
IEEE
226views Data Mining» more  ICDM 2006»
13 years 10 months ago
Converting Output Scores from Outlier Detection Algorithms into Probability Estimates
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Jing Gao, Pang-Ning Tan
DASFAA
2006
IEEE
136views Database» more  DASFAA 2006»
13 years 10 months ago
Mining Outliers in Spatial Networks
Outlier analysis is an important task in data mining and has attracted much attention in both research and applications. Previous work on outlier detection involves different type...
Wen Jin, Yuelong Jiang, Weining Qian, Anthony K. H...
ICDM
2008
IEEE
179views Data Mining» more  ICDM 2008»
13 years 11 months ago
Detection and Exploration of Outlier Regions in Sensor Data Streams
Sensor networks play an important role in applications concerned with environmental monitoring, disaster management, and policy making. Effective and flexible techniques are need...
Conny Franke, Michael Gertz
ICDM
2008
IEEE
176views Data Mining» more  ICDM 2008»
13 years 11 months ago
Inlier-Based Outlier Detection via Direct Density Ratio Estimation
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e., finding outliers in the test set based on the training set consisting only of inlier...
Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi...
COLCOM
2008
IEEE
13 years 11 months ago
Security through Collaboration in MANETs
It is well understood that Mobile Ad Hoc Networks (MANETs) are extremely susceptible to a variety of attacks, and traditional security mechanisms do not work well. Many security sc...
Wenjia Li, James Parker, Anupam Joshi
CIKM
2009
Springer
13 years 11 months ago
LoOP: local outlier probabilities
Many outlier detection methods do not merely provide the decision for a single data object being or not being an outlier but give also an outlier score or “outlier factor” sig...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...