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A Shrinking-Based Approach for Multi-Dimensional Data Analysis

Summary: Introduces “shrinking,” a gravity-inspired preprocessing method that moves points along density gradients to form compact, separated clusters. Multi-scale grid connected-component detection plus cluster-wise evaluation enables efficient clustering in low- and high-dimensional spaces. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9186
Venue
VLDB
Year
2003
Pagerank
5.093636e-05
Overall Rank
12,815 | 12.08%
DOI
10.1016/B978-012722442-8/50046-X

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BibTeX Citation

@article{shi_vldb03,
        title = {{A Shrinking-Based Approach for Multi-Dimensional Data Analysis}},
        author = {Shi, Yong and Song, Yuqing and Zhang, Aidong},
        journal = {PVLDB},
        series = {{VLDB} '03},
        doi = {10.1016/B978-012722442-8/50046-X},
        url = {https://doi.org/10.1016/B978-012722442-8/50046-X},
        year = {2003}
}

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