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Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering

Summary: Tutorial clarifies definitions across subspace, pattern-based, and correlation clustering in moderate-to-high dimensions. Highlights how differing formulations and assumptions across methods often address different problems rather than a single task. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9991
Venue
VLDB
Year
2008
Pagerank
5.093636e-05
Overall Rank
12,602 | 13.54%
DOI
10.14778/1454159.1454223

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BibTeX Citation

@article{kriegel_vldb08,
        title = {{Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering}},
        author = {Kriegel, Hans-Peter and Kröger, Peer and Zimek, Arthur},
        journal = {PVLDB},
        series = {{VLDB} '08},
        volume = {1},
        number = {1},
        pages = {1528--1531},
        doi = {10.14778/1454159.1454223},
        url = {https://doi.org/10.14778/1454159.1454223},
        year = {2008}
}

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