46 search results - page 1 / 10 » Local Subspace Based Outlier Detection |
IC3
2009
13 years 3 months ago
2009
Abstract. Existing studies in outlier detection mostly focus on detecting outliers in full feature space. But most algorithms tend to break down in highdimensional feature spaces b...
ICDE
2012
IEEE
11 years 7 months ago
2012
IEEE
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...
CIKM
2009
Springer
13 years 12 months ago
2009
Springer
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...
DAGSTUHL
2007
13 years 6 months ago
2007
Abstract. Increasingly large multimedia databases in life sciences, ecommerce, or monitoring applications cannot be browsed manually, but require automatic knowledge discovery in d...
KAIS
2006
13 years 5 months ago
2006
Outlier detection techniques are widely used in many applications such as credit card fraud detection, monitoring criminal activities in electronic commerce, etc. These application...