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)

Paper ID: hf805ed420e68c6b2
Venue: SIGMOD
Year: 2004
Pagerank: 5.529101e-05
Overall Rank: 7,433 | 50.03%
DOI: 10.1145/1007568.1007621

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
3,057	Dynamic Density Based Clustering	2017	SIGMOD	7.6965352e-05

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
32	BIRCH: An Efficient Data Clustering Method for Very Large Databases	1996	SIGMOD	0.00049737458
300	OPTICS: Ordering Points To Identify the Clustering Structure	1999	SIGMOD	0.00021810545
928	A Framework for Clustering Evolving Data Streams	2003	VLDB	0.00013025824
1,945	Incremental Clustering for Mining in a Data Warehousing Environment	1998	VLDB	9.3257256e-05
9,177	Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering	2001	SIGMOD	5.2125058e-05

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