Systems, methods, and devices for measuring similarity of and generating recommendations for unique items
First Claim
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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.
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Abstract
The disclosure herein provides methods, systems, and devices for measuring similarity of and generating recommendations for unique items. A recommendation system for generating recommendations of alternative unique items comprises an items information database, a penalty computation engine, a recommendation compilation engine, and one or more computers, wherein the penalty computation engine comprises a customizations filter, a condition filter, and a dissimilarity penalty calculator for determine the dissimilarity of attributes of alternative unique items from a plurality of selected items.
173 Citations
20 Claims
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1. A computer-implemented method for generating recommendations of alternative unique items, the computer-implemented method comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A recommendation system for generating recommendations of alternative unique items, the recommendation system comprising:
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an items information database configured to store data relating to unique items; a penalty computation engine configured to calculate a dissimilarity penalty, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between a plurality of selected items and an alternative item; a recommendation compilation engine configured to generate a recommendation of alternative unique items, wherein the recommendation compilation engine is configured to electronically communicate with the penalty computation engine to calculate dissimilarity penalties for each of a plurality of alternative unique items, the recommendation of alternative unique items comprising a ranking of at least a portion of the plurality of alternative unique items, the ranking based at least partially on the calculated dissimilarity penalties; and one or more computers configured to operate the recommendation compilation engine, wherein the one or more computers comprises a computer processor and an electronic storage medium. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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20. A computer-implemented method for generating recommended prices of unique items, the computer-implemented method comprising:
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receiving, at a computer system, electronic data indicating attributes for a new listing; selecting, using the computer system, a set of alternative unique items from a plurality of unique items for comparison to the attributes for the new listing; calculating, using the computer system, a dissimilarity penalty for each item in the set of alternative unique items, the dissimilarity penalty representing a similarity between the attributes for the new listing and attributes of the alternative unique items; generating, using the computer system, a set of similar alternative unique items comprising at least a portion of the set of alternative unique items, the set of similar alternative unique items generated based at least partially on the calculated dissimilarity penalties; generating, using the computer system, a recommended price for the new listing based at least partially on prices associated with the set of similar alternative unique items; wherein the computer system comprises a computer processor and electronic memory.
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Specification