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Continuous Outlier Detection in Data Streams: An Extensible Framework and State-Of-The-Art Algorithms

Summary: Extensible, open-source MOA extension for continuous, distance-based outlier detection over data streams. Four online algorithms for streaming outliers, including two novel methods; emphasis on faster runtimes, flexibility, and reduced space. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h1f0d1b8b07708b6f
Venue
SIGMOD
Year
2013
Pagerank
6.888581e-05
Overall Rank
3,950 | 73.53%
DOI
10.1145/2463676.2463691

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{georgiadis_sigmod13,
        title = {{Continuous Outlier Detection in Data Streams: An Extensible Framework and State-Of-The-Art Algorithms}},
        author = {Georgiadis, Dimitrios and Kontaki, Maria and Gounaris, Anastasios and Papadopoulos, Apostolos and Tsichlas, Kostas and Manolopoulos, Yannis},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2463691},
        url = {https://dl.acm.org/doi/10.1145/2463676.2463691},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
989 Data Cleaning: Overview and Emerging Challenges 2016 SIGMOD 0.00012638176
1,482 Distance-based Outlier Detection in Data Streams 2016 VLDB 0.00010501175
2,553 NETS: Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing 2019 VLDB 8.2846548e-05
3,048 Interactive Outlier Exploration in Big Data Streams 2014 VLDB 7.7012708e-05
7,749 PROUD: PaRallel OUtlier Detection for streams 2020 SIGMOD 5.4450584e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

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