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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
2744
Venue
SIGMOD
Year
1994
Pagerank
4.8812211e-05
Overall Rank
6,965 | 51.55%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
6,430 Semi-automatic, Self-adaptive Control of Garbage Collection Rates in Object Databases 1996 SIGMOD 5.066343e-05
7,524 On-line Reorganization in Object Databases 2000 SIGMOD 4.7180617e-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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