Creating optimal comparison criterion within associative memories

A method implemented using a computer in conjunction with a non-transitory computer readable storage medium and an associative memory comprising a plurality of data and a plurality of associations among the plurality of data, wherein the plurality of data is collected into associated groups, wherein the associative memory is configured to be queried based on at least indirect relationships among the plurality of data, the method comprising:

• receiving an input criteria at an input device in communication with the associative memory;
• generating, using the associative memory and an optimizer in communication with the input device and the associative memory, a multi-dimensional criteria file from the input criteria;
• converting, using the optimizer, the input criteria to numerical representations associated with expert weights;
• generating, using the optimizer, the multi-dimensional criteria file to include an optimized plurality of criteria relevant to the input criteria;
• and
• selecting, using the optimizer, the optimized plurality of criteria to compare entities associated with a specified attribute of a given perspective within the associative memory.

A system comprising:

• an associative memory comprising a plurality of data and a plurality of associations among the plurality of data, wherein the plurality of data is collected into associated groups, wherein the associative memory is configured to be queried based on at least one relationship, selected from a group that includes direct and indirect relationships, among the plurality of data, and wherein the associative memory is logically divided into a plurality of perspectives, and wherein the plurality of perspectives comprises a corresponding plurality of representations of subsets of the plurality of data;
• an input device configured to receive a first criteria file and a second criteria file, wherein the first criteria file comprises a first attribute category in a first perspective in the plurality of perspectives and a second attribute category in the first perspective, wherein the second criteria file comprises a third attribute category in the first perspective and a fourth attribute category in the first perspective, wherein the first attribute category and the third attribute category are equal, and wherein the second attribute category and the fourth attribute category are equal;
• and
• an optimizer configured to perform a multi-dimensional combination on the first criteria file and the second criteria file to form a third criteria file comprising a fifth attribute category in the first perspective and a sixth attribute category in the first perspective, wherein the fifth attribute category is equal to the first attribute category and the third attribute category, and wherein the sixth attribute category is equal to the second attribute category and the fourth attribute category;
• and
• wherein the optimizer converts input criteria to numerical representations associated with expert weights and generates the third criteria file to include an optimized plurality of criteria relevant to the input criteria;
• wherein the optimizer is further configured to select the optimized plurality of criteria to compare entities associated with a specified attribute of the first perspective within the associative memory.