Incremental Clustering for Mining in a Data Warehousing Environment
Summary: Proposes IncrementalDBSCAN to maintain DBSCAN clusters under daily warehouse updates. Updates affect only local neighborhoods, yielding identical results to DBSCAN and substantial speedups on spatial and WWW-log databases. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Martin Ester (University of Munich)
- 2. Hans-Peter Kriegel (University of Munich)
- 3. Jörg Sander (University of Munich)
- 4. Michael Wimmer (University of Munich)
- 5. Xiaowei Xu (University of Munich)
BibTeX Citation
@article{ester_vldb98,
title = {{Incremental Clustering for Mining in a Data Warehousing Environment}},
author = {Ester, Martin and Kriegel, Hans-Peter and Sander, Jörg and Wimmer, Michael and Xu, Xiaowei},
journal = {PVLDB},
series = {{VLDB} '98},
pages = {323--333},
year = {1998}
}
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4 | The R*-tree: An Efficient and Robust Access Method for Points and Rectangles | 1990 | SIGMOD | 0.001157935 |
| 27 | Fast Algorithms for Mining Association Rules | 1994 | VLDB | 0.00052255472 |
| 31 | BIRCH: An Efficient Data Clustering Method for Very Large Databases | 1996 | SIGMOD | 0.00050347119 |
| 56 | M-tree: An Efficient Access Method for Similarity Search in Metric Spaces | 1997 | VLDB | 0.00040719947 |
| 88 | Efficient and Effective Clustering Methods for Spatial Data Mining | 1994 | VLDB | 0.00035240327 |
| 905 | Maintenance of Data Cubes and Summary Tables in a Warehouse | 1997 | SIGMOD | 0.0001331508 |
| 5,779 | Multiple-View Self-Maintenance in Data Warehousing Environments | 1997 | VLDB | 6.0917725e-05 |
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