1 research outputs found
Local computation of answers to table queries on summary databases
We address the problem of evaluating table queries from a
summary database formed by a collection of pre-computed
tables on certain measure variables. We assume that every
table query asks for the distribution of a measure variable
of interest, and that the summary database contains tables
on the variable of interest as well as on other measure variables.
If the requested distribution is none of the base tables
and cannot be exactly derivable from none of them,
then the answer to the query will be the result of an estimation
procedure, which may bring up another measure
variable that is correlated to the measure variable of interest.
We give an estimation procedure that combines the
“divide-and-conquer” principle with tree computations