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Outlier Detection for High Dimensional Data

Summary: High-dimensional outlier detection; proximity-based definitions lose meaning in sparse spaces. Projection-based techniques analyze data projections to reveal meaningful outliers, addressing sparsity-induced ambiguity in high-dimensional data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3255
Venue
SIGMOD
Year
2001
Pagerank
6.0922282e-05
Overall Rank
4,552 | 68.34%
DOI
-

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