Biclustering and Boolean Matrix Factorization in Data Streams

Summary: Streaming bipartite clustering and BMF in data streams: one-pass, sublinear-space recovery of right-side clusters; second pass recovers left clusters. Empirical results: speedups over static baselines; quality within 2x; linear-time scaling; theory under planted models. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12262
Venue: VLDB
Year: 2020
Pagerank: 5.3766157e-05
Overall Rank: 8,739 | 40.05%
DOI: 10.14778/3401960.3401968

Incoming Non-self Citations Over Time

Authors

1. Stefan Neumann (University of Vienna)
2. Pauli Miettinen (University of Eastern Finland)

BibTeX Citation

@article{neumann_vldb20,
        title = {{Biclustering and Boolean Matrix Factorization in Data Streams}},
        author = {Neumann, Stefan and Miettinen, Pauli},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {10},
        pages = {1709--1722},
        doi = {10.14778/3401960.3401968},
        url = {https://doi.org/10.14778/3401960.3401968},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
11,530	The Gibbs–Rand Model	2022	PODS	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
451	Mergeable Summaries	2012	PODS	0.00018151445

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