Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Summary: Incremental data bubbles provide a compact, evolving summary for fast dynamic clustering. Quality-guided updates rebuild only bubbles that degrade compression, via split/merge, delivering faster summarization and preserved or improved clustering. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Samer Nassar (University of Alberta)
- 2. Jörg Sander (University of Alberta)
- 3. Corrine Cheng (University of Alberta)
BibTeX Citation
@inproceedings{nassar_sigmod04,
title = {{Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering}},
author = {Nassar, Samer and Sander, Jörg and Cheng, Corrine},
series = {{SIGMOD} '04},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1007568.1007621},
url = {https://dl.acm.org/doi/10.1145/1007568.1007621},
year = {2004}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,020 | Dynamic Density Based Clustering | 2017 | SIGMOD | 7.8445412e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 31 | BIRCH: An Efficient Data Clustering Method for Very Large Databases | 1996 | SIGMOD | 0.00050347119 |
| 291 | OPTICS: Ordering Points To Identify the Clustering Structure | 1999 | SIGMOD | 0.00022264197 |
| 907 | A Framework for Clustering Evolving Data Streams | 2003 | VLDB | 0.00013309819 |
| 1,907 | Incremental Clustering for Mining in a Data Warehousing Environment | 1998 | VLDB | 9.501636e-05 |
| 9,013 | Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering | 2001 | SIGMOD | 5.3321448e-05 |
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