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» Outlier Detection with Kernel Density Functions
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DEXA
2010
Springer
266views Database» more  DEXA 2010»
13 years 6 months ago
DBOD-DS: Distance Based Outlier Detection for Data Streams
Data stream is a newly emerging data model for applications like environment monitoring, Web click stream, network traffic monitoring, etc. It consists of an infinite sequence of d...
Md. Shiblee Sadik, Le Gruenwald
ICDM
2010
IEEE
232views Data Mining» more  ICDM 2010»
13 years 2 months ago
gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration
Community detection is an important task for mining the structure and function of complex networks. Many pervious approaches are difficult to detect communities with arbitrary size...
Heli Sun, Jianbin Huang, Jiawei Han, Hongbo Deng, ...
CIKM
2010
Springer
13 years 3 months ago
Top-Eye: top-k evolving trajectory outlier detection
The increasing availability of large-scale location traces creates unprecedent opportunities to change the paradigm for identifying abnormal moving activities. Indeed, various asp...
Yong Ge, Hui Xiong, Zhi-hua Zhou, Hasan Ozdemir, J...
PAKDD
2005
ACM
142views Data Mining» more  PAKDD 2005»
13 years 10 months ago
Dynamic Cluster Formation Using Level Set Methods
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
Andy M. Yip, Chris H. Q. Ding, Tony F. Chan
SDM
2010
SIAM
165views Data Mining» more  SDM 2010»
13 years 6 months ago
Direct Density Ratio Estimation with Dimensionality Reduction
Methods for directly estimating the ratio of two probability density functions without going through density estimation have been actively explored recently since they can be used...
Masashi Sugiyama, Satoshi Hara, Paul von Büna...