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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
3603
Venue
SIGMOD
Year
2004
Pagerank
5.6539603e-05
Overall Rank
7,291 | 49.98%
DOI
10.1145/1007568.1007621

Incoming Non-self Citations Over Time

Authors

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)

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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)

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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