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Self-Adaptive, On-Line Reclustering of Complex Object Data

Summary: Self-adaptive, on-line reclustering for large, heterogeneous objects in object-oriented databases. Architecture decomposes clustering into concurrent modules—statistics collection, cluster analysis, and reorganization—to adapt in real time to shifting usage patterns, with experiments showing reduced object-access miss rates. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
2806
Venue
SIGMOD
Year
1994
Pagerank
5.682335e-05
Overall Rank
7,174 | 50.79%
DOI
10.1145/191839.191924

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{jr_sigmod94,
        title = {{Self-Adaptive, On-Line Reclustering of Complex Object Data}},
        author = {William J. McIver, Jr. and King, Roger},
        series = {{SIGMOD} '94},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/191839.191924},
        url = {https://dl.acm.org/doi/10.1145/191839.191924},
        year = {1994}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
7,227 Semi-automatic, Self-adaptive Control of Garbage Collection Rates in Object Databases 1996 SIGMOD 5.66667e-05
7,944 On-line Reorganization in Object Databases 2000 SIGMOD 5.5181056e-05
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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.

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