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ICDM
2009
IEEE
150views Data Mining» more  ICDM 2009»
15 years 3 months ago
Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection
Anomaly detection is an important data mining task. Most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. A r...
Xiao Yu, Lu An Tang, Jiawei Han
CEAS
2011
Springer
14 years 5 months ago
Spam or ham?: characterizing and detecting fraudulent "not spam" reports in web mail systems
Web mail providers rely on users to “vote” to quickly and collaboratively identify spam messages. Unfortunately, spammers have begun to use bots to control large collections o...
Anirudh Ramachandran, Anirban Dasgupta, Nick Feams...
ACCV
2010
Springer
15 years 1 months ago
Stream-based Active Unusual Event Detection
We present a new active learning approach to incorporate human feedback for on-line unusual event detection. In contrast to most existing unsupervised methods that perform passiv...
Chen Change Loy, Tao Xiang, Shaogang Gong
ICIP
2004
IEEE
16 years 7 months ago
Unsupervised motion detection using a markovian temporal model with global spatial constraints
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Pierre-Marc Jodoin, Max Mignotte
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
16 years 7 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