@inproceedings{DBLP:conf/vldb/MalvestutoM89, author = {Francesco M. Malvestuto and Marina Moscarini}, editor = {Peter M. G. Apers and Gio Wiederhold}, title = {Aggregate Evaluability in Statistical Databases}, booktitle = {Proceedings of the Fifteenth International Conference on Very Large Data Bases, August 22-25, 1989, Amsterdam, The Netherlands}, publisher = {Morgan Kaufmann}, year = {1989}, isbn = {1-55860-101-5}, pages = {279-286}, ee = {db/conf/vldb/MalvestutoM89.html}, crossref = {DBLP:conf/vldb/89}, bibsource = {DBLP, http://dblp.uni-trier.de} }

Usually a statistical database contains many summary tables representing the distribution of the same statistical variable over the classes ofas many partitions of a certain universe of objects. Existing query systems allow only queries on single tables. Indeed, in most cases additional queries can be evaluated by combining the information contained in similar tables in a suitable way.

In order to improve the responsiveness of the database and allow an integrated use of the stored information, we propose to inform the database system of the relationship among the partitions adopted in the tables.
Such a relationship, called *intersection dependency*, states which classes of the partitions have a non-empty intersection and can be represented by a uniform multipartite hypergraph, called *intersection* hypergraph.

On the grounds of the algebraic properties of the intel section hypergraph and under the assumption of data additivity, we shall provide a characterization of evaluable queries, which allows us to define polynomial-time procedures both for testing evaluability and for evaluating queries.

*Copyright © 1989 by the VLDB Endowment.
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