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Real-Time Distance-Based Outlier Detection in Data Streams

Summary: CPOD introduces a core-point with multi-distance indexing for real-time distance-based outlier detection in streaming data on edge devices. Memory-efficient; up to 73x faster than MCOD/NETS/M_MCOD across six real-world and one synthetic dataset by shrinking neighbor search. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12518
Venue
VLDB
Year
2021
Pagerank
7.7214053e-05
Overall Rank
3,135 | 78.50%
DOI
10.14778/3425879.3425885

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{tran_vldb21,
        title = {{Real-Time Distance-Based Outlier Detection in Data Streams}},
        author = {Tran, Luan and Mun, Min Y. and Shahabi, Cyrus},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {2},
        pages = {141--153},
        doi = {10.14778/3425879.3425885},
        url = {https://doi.org/10.14778/3425879.3425885},
        year = {2021}
}

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