Automatic determination of OLAP cube dimensions
First Claim
1. A computerized method for automatically determining at least one variable dimension for a multi-dimensional database table, said multi-dimensional database table also comprising at least one pre-defined measure dimension for storing values of at least one measure type, the method comprising the steps of:
- determining a set of input records, each of said input records comprising a value of at least a first measure type and associated values of a plurality of variable types, said variable types representing candidates for a variable dimension; and
calculating a regression function for use as a prediction model of said value of said measure type, said regression function depending on values of a subset of up to M most significant of said plurality of variable types; and
determining said most significant variable types as variable dimensions of a multi-dimensional database table.
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Abstract
Means and a computerized method for determining variable dimensions for a multi-dimensional database table, whereby the database table also comprises at least one pre-defined measure dimension for storing values of one or more measure types. Input records are treated as an implicit, yet unknown functional relationship between the measure types as dependent variables and the variable types as independent variables. A regression function is then calculated and used as a prediction model for the measure types based on the variable types, using the input records. The most significant variable types contributing to this prediction model are selected as variable dimensions for the database table.
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14 Claims
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1. A computerized method for automatically determining at least one variable dimension for a multi-dimensional database table, said multi-dimensional database table also comprising at least one pre-defined measure dimension for storing values of at least one measure type, the method comprising the steps of:
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determining a set of input records, each of said input records comprising a value of at least a first measure type and associated values of a plurality of variable types, said variable types representing candidates for a variable dimension; and
calculating a regression function for use as a prediction model of said value of said measure type, said regression function depending on values of a subset of up to M most significant of said plurality of variable types; and
determining said most significant variable types as variable dimensions of a multi-dimensional database table. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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Specification