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Clustering Stream Data by Exploring the Evolution of Density Mountain

Summary: EDMStream models streaming distributions as evolving density mountains, tracking cluster births, deaths, splits, and merges. Specialized data structures and filtering enable real-time updates, delivering 7–15× faster response than prior methods with comparable cluster quality. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11939
Venue
VLDB
Year
2018
Pagerank
6.2618226e-05
Overall Rank
5,335 | 63.40%
DOI
10.1145/3164135.3164136

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{gong_vldb18,
        title = {{Clustering Stream Data by Exploring the Evolution of Density Mountain}},
        author = {Gong, Shufeng and Zhang, Yanfeng and Yu, Ge},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {4},
        pages = {393--405},
        doi = {10.1145/3164135.3164136},
        url = {https://doi.org/10.1145/3164135.3164136},
        year = {2018}
}

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