Method and medium for recommending a personalized ensemble

1. A computer-implemented method for generating a recommendation of a personalized ensemble, said computer-implemented method comprising:

accessing, by a computer system, customer data associated with a customer to achieve accessed customer data;

accessing, by said computer system, rules, wherein said rules comprise a set of constraints pertaining to valid and invalid combinations of retail items, wherein said retail items have tags that describe respective retail items, and wherein said tags comprise subsets of tags;

determining, by said computer system, a quantity of two-dimensional images that can be displayed in a single view on a display of the computer system;

assigning the quantity of two-dimensional images as a predetermined threshold number;

reducing, by said computer system, said subsets of tags from a first number to said predetermined threshold number

said first number of tags being a number of all tags fitting a particular descriptor,

said reducing said subsets of tags to said predetermined threshold number by continuing to add additional descriptors to further narrow said first number of tags until less than said predetermined threshold number is reached;

displaying, on a display screen of said computer system, a plurality of two-dimensional images corresponding to said reduced subset of tags associated with said retail items, wherein said plurality of two-dimensional images are scrollable around an outer surface of an unrendered three-dimensional sphere, wherein each of said plurality of two-dimensional images can be rotated concurrently in any direction about a center point of said sphere;

receiving, by said computer system, a selection of one of said plurality of two-dimensional images to achieve a received selection; and

dynamically generating and displaying, by said computer system and based on said accessed customer data, said accessed rules and said received selection, a recommendation of a personalized ensemble for said customer.

2. The computer-implemented method of claim 1 , wherein said accessing, by said computer system, customer data further comprises:

accessing said customer data, wherein at least a subset of said customer data is not required to be associated with said selection of one of said retail items for purchase.

3. The computer-implemented method of claim 1 , wherein said accessing, by said computer system, customer data further comprises:

accessing said customer data from a retailer.

4. The computer-implemented method of claim 1 , wherein said accessing, by said computer system, customer data further comprises:

accessing purchase history of said customer.

5. The computer-implemented method of claim 1 , wherein said accessing, by said computer system, customer data further comprises:

accessing social media information of said customer.

6. The computer-implemented method of claim 1 , wherein said by said computer system, dynamically generating a recommendation of a personalized ensemble comprises:

based on said accessed customer data, said accessed rules and said received selection, dynamically generating a recommendation of a personalized ensemble comprising coordinated items.

7. The computer-implemented method of claim 1 , wherein said recommendation of said personalized ensemble is unique to said customer.

8. The computer-implemented method of claim 1 , further comprising:

generating, by said computer system, a correlation table based on said accessed customer data.

9. The computer-implemented method of claim 1 , further comprising:

based on said accessed customer data, said accessed rules and said received selection, by said computer system, dynamically generating, by said computer system, a hierarchy of recommendations.

10. The computer-implemented method of claim 1 , further comprising:

on said display screen and by said computer system, displaying, by said computer system, said recommendation in proximity to said selection of said one of said plurality of two-dimensional images.

11. A non-transitory computer-readable storage medium having instructions embodied therein when executed cause a computer system to perform a method for generating a recommendation of a personalized ensemble, said method comprising:

accessing customer data associated with a customer to achieve accessed customer data;

accessing rules, wherein said rules comprise a set of constraints pertaining to valid and invalid combinations of retail items, wherein said retail items have tags that describe respective retail items, and wherein said tags comprise subsets of tags;

determining, by said computer system, a quantity of two-dimensional images that can be displayed in a single view on a display of the computer system;

assigning the quantity of two-dimensional images as a predetermined threshold number;

reducing, by said computer system, said subsets of tags from a first number to said predetermined threshold number

said first number of tags being a number of all tags fitting a particular descriptor,

said reducing said subsets of tags to said predetermined threshold number by continuing to add additional descriptors to further narrow said first number of tags until less than said predetermined threshold number is reached;

displaying a plurality of two-dimensional images corresponding to said reduced subset of tags associated with said retail items;

receiving a selection of at least one of said plurality of two-dimensional images, wherein said plurality of two-dimensional images are scrollable around an outer surface of an unrendered three-dimensional sphere, said plurality of two-dimensional images concurrently rotatable in any direction about a center point of said sphere;

bookmarking said selection of at least one of said plurality of two-dimensional images respective a plurality of retail items; and

dynamically generating and displaying a recommendation of a personalized ensemble for said customer based on said one or more bookmarked retail items and said accessed customer data.

12. The non-transitory computer-readable storage medium of claim 11 , wherein said accessing customer data further comprises:

accessing said customer data, wherein at least a subset of said customer data is not required to be associated with said selection of one of said retail items for purchase.

13. The non-transitory computer-readable storage medium of claim 11 , wherein said accessing customer data comprises:

accessing purchase history of said customer.

14. The non-transitory computer-readable storage medium of claim 11 , wherein said accessing customer data comprises:

accessing social media information of said customer.

15. The non-transitory computer-readable storage medium of claim 11 , wherein said recommendation of a personalized ensemble is unique to said customer.

16. The non-transitory computer-readable storage medium of claim 11 , further comprising:

displaying said recommendation of said personalized ensemble.

17. The non-transitory computer-readable storage medium of claim 11 , further comprising:

displaying said selected bookmarked item in a filmstrip format.