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A Framework for Clustering Uncertain Data

Summary: Clustering uncertain data via a general, model-driven framework; integrates visualization to quantify how uncertainty propagates into clustering outcomes. ELKI 0.7 implements diverse algorithms, distance measures, indexing, evaluation metrics, and visualization tools across multiple uncertainty models. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11285
Venue
VLDB
Year
2015
Pagerank
6.068841e-05
Overall Rank
5,843 | 59.92%
DOI
10.14778/2824032.2824083

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{schubert_vldb15,
        title = {{A Framework for Clustering Uncertain Data}},
        author = {Schubert, Erich and Koos, Alexander and Emrich, Tobias and Züfle, Andreas and Schmid, Klaus Arthur and Zimek, Arthur},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {12},
        pages = {1976--1979},
        doi = {10.14778/2824032.2824083},
        url = {https://doi.org/10.14778/2824032.2824083},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
1,792 MacroBase: Prioritizing Attention in Fast Data 2017 SIGMOD 9.7436856e-05
4,627 Pivot-based Metric Indexing 2017 VLDB 6.5963674e-05
9,165 Dimensional Testing for Reverse k-Nearest Neighbor Search 2017 VLDB 5.3101672e-05
11,420 F3 KM: Federated, Fair, and Fast k-means 2023 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
78 ULDBs: Databases with Uncertainty and Lineage 2006 VLDB 0.00036571789
331 Trio: A System for Data, Uncertainty, and Lineage 2006 VLDB 0.00020936658
12,238 Interactive Data Mining with 3D-Parallel-Coordinate-Trees 2013 SIGMOD 5.093636e-05
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