StreamMiner: A Classifier Ensemble-based Engine to Mine Concept-drifting Data Streams

Summary: StreamMiner is a random-decision-tree ensemble engine for mining concept-drifting streams. It detects drift online without labels and systematically selects historical data and new chunks to retrain an adaptive model. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 9298
Venue: VLDB
Year: 2004
Pagerank: 5.093636e-05
Overall Rank: 12,787 | 12.27%
DOI: 10.1016/B978-012088469-8.50121-2

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Wei Fan (International Business Machines Thomas J. Watson Research)

BibTeX Citation

@article{fan_vldb04,
        title = {{StreamMiner: A Classifier Ensemble-based Engine to Mine Concept-drifting Data Streams}},
        author = {Fan, Wei},
        journal = {PVLDB},
        series = {{VLDB} '04},
        pages = {1257--1268},
        doi = {10.1016/B978-012088469-8.50121-2},
        url = {https://doi.org/10.1016/B978-012088469-8.50121-2},
        year = {2004}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

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.

Rank	Cited Paper	Year	Venue	Pagerank
26	Models and Issues in Data Stream Systems	2002	PODS	0.00052982574
82	Space-Efficient Online Computation of Quantile Summaries	2001	SIGMOD	0.00036378991
2,171	Multi-Dimensional Regression Analysis of Time-Series Data Streams	2002	VLDB	9.0406168e-05
3,920	Continually Evaluating Similarity-Based Pattern Queries on a Streaming Time Series	2002	SIGMOD	7.0171134e-05

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