Insight and algorithmic clustering for automated synthesis

A method for selecting at least one object from a plurality of multidimensional objects, comprising:

• receiving inputs with respect to the plurality of multidimensional objects comprising hidden dimensions from a plurality of sources;
• receiving at least one tuning parameter that impacts at least one hidden dimension of the plurality of multidimensional objects;
• generating a subset of multidimensional objects from the plurality of multidimensional objects based on at least one selection criterion, the subset of multidimensional objects having fewer multidimensional objects than the plurality of multidimensional objects;
• generating a quantitative analysis of the subset of multidimensional objects, based on:
• the respective inputs received from the subset of the plurality of sources having fewer sources than the plurality of sources,
• characteristics of the respective source from which the respective inputs are received,
• the at least one tuning parameter;
• and
• the at least one selection criterion;
• using a multidimensional distance function to reduce a number of dimensions of the plurality of multidimensional objects by forming clusters;
• automatically selecting at least one object as an optimum object, based on at least the quantitative analysis and the clusters;
• receiving feedback relating to the at least one selected object;
• and
• automatically updating a characteristic of the respective source based on the feedback.

A system for selecting an object from a group of multidimensional objects, comprising:

• an input port configured to:
• receive inputs with respect to the group of multidimensional objects from a plurality of sources, each object having a plurality of hidden dimensions;
• receive at least one tuning parameter that impacts at least one hidden dimension of the group of multidimensional objects;
• at least one automated processor, configured to:
• generate a subset of multidimensional objects from the group of multidimensional objects based on at least one selection criterion, the subset of multidimensional objects having fewer multidimensional objects than the group of multidimensional objects;
• generate a quantitative analysis of the subset of multidimensional objects, based on:
• the respective inputs received from the subset of the plurality of sources having fewer sources than the plurality of sources,
• characteristics of a respective source of the subset of the plurality of sources from which a respective input is received,
• at least one tuning parameter;
• and
• at least one selection criterion,
• use a multidimensional distance function to reduce a number of dimensions of the group of multidimensional objects to form clusters, and to select at least one object based on at least the quantitative analysis and clustering;
• at least one output port configured to convey data selectively associated with the at least one selected object;
• and
• the input port being configured to receive feedback relating to the at least one selected object, wherein the at least one automated processor is further configured to automatically update a characteristic of the respective source based on the feedback.