StreamMiner: A Classifier Ensemble-based Engine to Mine Concept-drifting Data Streams
Summary: StreamMiner, a random-forest–style ensemble engine, mines concept-drifting data streams. It enables on-the-fly drift detection without ground truth and systematic old/new data chunk selection to compute an optimal adaptive model. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Wei Fan
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 43 | Models and Issues in Data Stream Systems | 2002 | PODS | 0.00072660894 |
| 126 | Space-Efficient Online Computation of Quantile Summaries | 2001 | SIGMOD | 0.00044753012 |
| 2,448 | Multi-Dimensional Regression Analysis of Time-Series Data Streams | 2002 | VLDB | 8.7935134e-05 |
| 4,210 | Continually Evaluating Similarity-Based Pattern Queries on a Streaming Time Series | 2002 | SIGMOD | 6.3509527e-05 |
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