Statistical and Scientific Database Issues
IEEE Transactions on Software Engineering
Statistical treatment of the information content of a database
Information Systems
Modelling large bases of categorical data with acyclic schemes
Proceedings on International conference on database theory
On the Desirability of Acyclic Database Schemes
Journal of the ACM (JACM)
Graphs and Hypergraphs
Decomposing complex contingency tables to reduce storage requirements
SSDBM'86 Proceedings of the 3rd international workshop on Statistical and scientific database management
Aggregate evaluability in statistical databases
VLDB '89 Proceedings of the 15th international conference on Very large data bases
ADAMS: an object-oriented system for epidemiological data manipulation
SAC '93 Proceedings of the 1993 ACM/SIGAPP symposium on Applied computing: states of the art and practice
A universal-scheme approach to statistical databases containing homogeneous summary tables
ACM Transactions on Database Systems (TODS)
Query Evaluability in Statistical Databases
IEEE Transactions on Knowledge and Data Engineering
Mefisto: A Functional Model for Statistical Entities
IEEE Transactions on Knowledge and Data Engineering
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A compatible categorical data base can be viewed as a single (contingency) table by taking the maximum-entropy extension of the component tables. Such a view, here called universal table model, is needed to answer a user who wishes “cross-classified” categorical data, that is, categorical data resulting from the combination of the information contents of two or more base tables. In order to implement a universal table interface we make use of a query-optimization procedure, which is able to generate an appropriate answer both in the case that the asked data are present in the data base and in the case that they are not and, then, have to be estimated