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A Dynamic Clustering Technique For Physical Database Design

Summary: Dynamic clustering reframed as partitioning of attribute space, directed by a discriminator sequence and analyzed partition count. Extended K-d tree directs partitioning; results show gains vs single-attribute clustering and inverted-file methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
2196
Venue
SIGMOD
Year
1980
Pagerank
9.201869e-05
Overall Rank
2,082 | 85.72%
DOI
10.1145/582250.582280

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{chang_sigmod80,
        title = {{A DYNAMIC CLUSTERING TECHNIQUE FOR PHYSICAL DATABASE DESIGN}},
        author = {Chang, J. M. and Fu, K. S.},
        series = {{SIGMOD} '80},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/582250.582280},
        url = {https://dl.acm.org/doi/10.1145/582250.582280},
        year = {1980}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
115 A Decomposition Storage Model 1985 SIGMOD 0.00032338948
3,771 Query Processing Method for Multi-Attribute Clustered Relations 1990 VLDB 7.1391812e-05
6,451 Efficient Search of Multidimensional B-Trees 1995 VLDB 5.8751993e-05
13,217 MULTIKEY RETRIEVAL from K-d TREES and QUAD-TREES 1985 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

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

Rank Cited Paper Year Venue Pagerank
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