Systems, methods, and devices for measuring similarity of and generating recommendations for unique items

A computer-implemented method for generating recommendations of alternative unique items, the computer-implemented method comprising:

• receiving electronic data indicating a selection of a selected unique item;
• generating, using a computer system, a set of base unique items, the set of base unique items comprising the selected unique item and at least one additional unique item, wherein the selected unique item and the at least one additional unique item each comprise a plurality of attributes;
• generating, using the computer system, a set of alternative unique items for comparison to the set of base unique items, the set of alternative unique items comprising a plurality of alternative unique items each comprising a plurality of attributes;
• calculating, using the computer system, for each of the plurality of alternative unique items of the set of alternative unique items, a dissimilarity penalty, wherein the dissimilarity penalty is based at least partially on a magnitude of dissimilarity between an attribute value of the plurality of attributes of the alternative unique item and a plurality of attribute values of the plurality of attributes of the set of base unique items;
• and
• generating, using the computer system, a recommendation of one or more alternative unique items, the recommendation based at least partially on a ranking of the plurality of alternative unique items using the calculated dissimilarity penalties,
• wherein the computer system comprises a computer processor and electronic memory.

A system for generating recommendations of alternative unique items, the system comprising:

• one or more computer readable storage devices configured to store a plurality of computer executable instructions;
• and
• one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the system to:
• receive electronic data indicating a selection of a selected unique item;
• generate a set of base unique items, the set of base unique items comprising the selected unique item and at least one additional unique item, wherein the selected unique item and the at least one additional unique item each comprise a plurality of attributes;
• generate a set of alternative unique items for comparison to the set of base unique items, the set of alternative unique items comprising a plurality of alternative unique items each comprising a plurality of attributes;
• calculate, for each of the plurality of alternative unique items of the set of alternative unique items, a dissimilarity penalty, wherein the dissimilarity penalty is based at least partially on a magnitude of dissimilarity between an attribute value of the plurality of attributes of the alternative unique item and a plurality of attribute values of the plurality of attributes of the set of base unique items;
• and
• generate a recommendation of one or more alternative unique items, the recommendation based at least partially on a ranking of the plurality of alternative unique items using the calculated dissimilarity penalties.