DBScholar

Back to papers

Distance-Based Outlier Detection: Consolidation and Renewed Bearing

Summary: Consolidates distance-based outlier detection designs and optimization strategies in a unified framework. A factorial study across diverse real datasets shows no universally best configuration, yielding state-of-the-art algorithms and guidance on when optimizations prevail. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10221
Venue
VLDB
Year
2010
Pagerank
5.191171e-05
Overall Rank
9,952 | 31.73%
DOI
10.14778/1920841.1921021

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{orair_vldb10,
        title = {{Distance-Based Outlier Detection: Consolidation and Renewed Bearing}},
        author = {Orair, Gustavo H. and Teixeira, Carlos H. C. and Meira, Jr., Wagner and Wang, Ye and Parthasarathy, Srinivasan},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {2},
        pages = {1469--1480},
        doi = {10.14778/1920841.1921021},
        url = {https://doi.org/10.14778/1920841.1921021},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
8,230 TOD: GPU-accelerated Outlier Detection via Tensor Operations 2023 VLDB 5.4619615e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers