DBScholar

Back to papers

PROUD: PaRallel OUtlier Detection for streams

Summary: PROUD: PaRallel OUtlier Detection for streams, a Flink-based engine for continuous, multi-parameter distance-based outlier detection. Extensible, configurable parallel techniques; simple ingestion API; live metrics; open-source storage for future analysis. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5923
Venue
SIGMOD
Year
2020
Pagerank
5.5908113e-05
Overall Rank
7,587 | 47.95%
DOI
10.1145/3318464.3384688

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{toliopoulos_sigmod20,
        title = {{PROUD: PaRallel OUtlier Detection for streams}},
        author = {Toliopoulos, Theodoros and Bellas, Christos and Gounaris, Anastasios and Papadopoulos, Apostolos},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3384688},
        url = {https://dl.acm.org/doi/10.1145/3318464.3384688},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
4,814 METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection 2024 VLDB 6.4955135e-05
8,230 TOD: GPU-accelerated Outlier Detection via Tensor Operations 2023 VLDB 5.4619615e-05
10,189 Adaptive Outlier Detection over Data Stream 2026 SIGMOD 5.093636e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 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