Optimal solution identification system and method
AssigneeThe Nielsen Company (US), LLC
InventorsKevin D. Karty, Kamal M. Malek, David B. Teller
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Abstract
A method, computer program product, and computer system for receiving, at a computing device, data from at least one user, wherein at least a portion of the data is associated with the plurality of attribute variants. A variant relationship between one or more pairs of attribute variants of the plurality of attribute variants is determined based upon, at least in part, at least the portion of the data. The distance between the one or more pairs of objects is adjusted based upon, at least in part, the variant relationship between the one or more pairs of attribute variants of the plurality of attribute variants.
Claims21
A computer-implemented method for performing analysis on a set of objects having a plurality of attributes and a related distance metric between pairs of objects, the method comprising:
- calculating, at a computing device, utility data associated with attributes of a first type and a second type;
- determining, at the computing device, a relationship between the first type and the second type of attributes by calculating a first difference metric between the utility values for the first type of attribute, and calculating a second difference metric between the utility values for the second type of attribute;
- and
- determining, at the computing device, a relative attribute importance based on which of the first type of attribute or the second type of attribute affects the pairs of objects to a greater degree, wherein the relative attribute importance is based on a first within-attribute dispersion of a variant batting average of the first type of attribute and a second within-attribute dispersion of a variant batting average of the second type of attribute;
- determining, at the computing device, a correlation between the first type of attribute and the second type of attribute;
- determining, at the computing device, a variant similarity by transforming the correlation between the first type of attribute and the second type of attribute, wherein the correlation between the first type of attribute and the second type of attribute is transformed into the variant similarity by taking one over one plus e to the negative power of the correlation times a scale parameter plus a location parameter;
- and
- improving a search efficiency computation by adjusting, at the computing device, the related distance metric between the pairs of objects in the set based upon the relative attribute importance and the variant similarity.
A computing system for performing analysis on a set of objects having a plurality of attributes and a related distance metric between pairs of objects, the computing system including a processor and a memory configured to:
- calculate utility data associated with attributes of a first type and a second type;
- determine a relationship between the first type and the second type of attributes by calculating a first difference metric between the utility values for the first type of attribute and calculating a second difference metric between the utility values for the second type of attribute;
- and
- determine a relative attribute importance based on which of the first type of attribute or the second type of attribute affects the pairs of objects to a greater degree, wherein the relative attribute importance is based on a first within-attribute dispersion of a variant batting average of the first type of attribute and a second within-attribute dispersion of a variant batting average of the second type of attribute;
- determine a correlation between the first type of attribute and the second type of attribute;
- determine a variant similarity by transforming the correlation between the first type of attribute or the second type of attribute, wherein the correlation between the first type of attribute and the second type of attribute is transformed into the variant similarity by taking one over one plus e to the negative power of the correlation times a scale parameter plus a location parameter;
- and
- improve a search efficiency computation by adjusting the related distance metric between the pairs of objects in the set based upon the relative attribute importance and the variant similarity.
A computer readable storage medium comprising instructions which, when executed by a processor, cause the processor to, at least:
- calculate utility data associated with attributes of a first type and a second type;
- determine a relationship between the first type and the second type of attributes by calculating a first difference metric between the utility values for the first type of attribute, and calculating a second difference metric between the utility values for the second type of attribute;
- and
- determine a relative attribute importance based on which of the first type of attribute or the second type of attribute affects pairs of objects to a greater degree, wherein the relative attribute importance is based on a first within-attribute dispersion of a variant batting average of the first type of attribute and a second within-attribute dispersion of a variant batting average of the second type of attribute;
- determine a correlation between the first type of attribute and the second type of attribute;
- determine a variant similarity by transforming the correlation between the first type of attribute or the second type of attribute, wherein the correlation between the first type of attribute and the second type of attribute is transformed into the variant similarity by taking one over one plus e to the negative power of the correlation times a scale parameter plus a location parameter;
- and
- improve a search efficiency computation by adjusting the related distance metric between the pairs of objects in the set based upon the relative attribute importance and the variant similarity.
Dependencies are inferred from the claim text.