1. 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 item; updating, using a computer system, a set of base items to include the selected item, wherein the selected item and the base items each comprise a plurality of attributes; determining, using the computer system, a set of base attributes from the plurality of attributes of the items in the set of base items to use for determining the similarity of alternative unique items to the set of base items; selecting, using the computer system, a set of alternative unique items from a plurality of unique items for comparison to the set of base items; calculating, using the computer system, a first dissimilarity penalty for a first attribute of the set of base attributes for the set of alternative unique items at least partially based on a magnitude of dissimilarity between a value of the first attribute of the set of alternative items and the values of the first attribute of the set of base attributes; calculating, using the computer system, a second dissimilarity penalty for a second attribute of the set of base attributes for the set of alternative unique items at least partially based on a magnitude of dissimilarity between a value of the second attribute of the set of alternative items and the values of the second attribute of the set of base attributes; and generating, using the computer system, a recommendation of alternative unique items, the recommendation comprising ranking of at least a portion of the plurality of the set of alternative unique items, the ranking based at least partially on the generated dissimilarity penalties; wherein the computer system comprises a computer processor and electronic memory.