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Handling Summary Information In A Database: Derivability

Summary: Defines a schema of summary data as a relation between object classifications and attribute domains; introduces reclassification rules as semantic links. Employs set-theoretic lemmata as an inference mechanism to test derivability and derive summaries, improving usability and logical data independence (statistical examples). (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
2149
Venue
SIGMOD
Year
1981
Pagerank
6.2824978e-05
Overall Rank
4,316 | 70.01%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
12,957 Aggregate Evaluability In Statistical Databases 1989 VLDB 4.1905499e-05
12,968 The derivation problem for summary data 1988 SIGMOD 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
7 Extending the Data Base Relational Model to Capture More Meaning 1979 SIGMOD 0.0015464728
5,009 IAM:: An Inferential Abstract Modeling Approach to Design of Conceptual Schema 1977 SIGMOD 5.757357e-05
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