Cognitive fashion product recommendation system, computer program product, and method

1. A computer-implemented method, executed on a computing device, comprising:

training, according to a process, a plurality of neural networks from a plurality of images, wherein each neural network corresponds to an attribute of the plurality of images, a category of the plurality of images, or a sub-category of the plurality of images, wherein the process is selected and identified to process one or more images of a fashion category and/or a fashion sub-category to generate one or more fashion-ability scores each comprising a numerical representation of a corresponding fashion product defined in a corresponding image of the corresponding fashion product;

for each trained neural network, scoring each of the plurality of images against each attribute that the neural network is trained for, and generating one or more scored vectors wherein each scored vector corresponds to a particular attribute used to train the neural network;

joining each of the scored vectors for each of the plurality of images to form a multi-dimensional vector corresponding to a visual representation of each of the plurality of images;

associating, at the computing device, one or more fashion products on a website with a user accessing the website, wherein each of the one or more fashion products associated with the user on the website is assigned a priority score based upon, at least in part a fashion browsing sequence of the user;

generating the one or more fashion-ability scores such that the one or more fashion-ability scores are representative of the one or more fashion products on the website, by selecting an attribute and retrieving the scored vector that is trained for the selected attribute;

in response to retrieving the scored vector trained for the selected attribute, producing the one or more fashion-ability scores that represents one or more fashion products corresponding to the selected attribute; and

providing one or more recommendations to the user for the one or more fashion products on the website based upon, at least in part, one or more fashion-ability scores representative of the one or more fashion products associated with the user on the website and the one or more fashion-ability scores representative of the one or more fashion products on the website, wherein the one or more recommendations are presented to the user in order of the priority score assigned to the one or more fashion products on the website.

2. The computer-implemented method of claim 1 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing one or more recommendations for one or more newly added fashion products based upon, at least in part, the one or more fashion-ability scores representative of the one or more fashion products associated with the user on the website and one or more fashion-ability scores representative of the one or more newly added fashion products.

3. The computer-implemented method of claim 1 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website with a fashion-ability score within a threshold of the fashion-ability score of the one or more fashion products associated with the user.

4. The computer-implemented method of claim 3 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for one or more fashion products on the website from a different fashion category than a fashion category of the one or more fashion products associated with the user.

5. The computer-implemented method of claim 1 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website with a fashion-ability score greater than the fashion-ability score of the one or more fashion products associated with the user.

6. The computer-implemented method of claim 1 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website from the same fashion category as the fashion products associated with the user that have fashion-ability scores within a threshold of the fashion-ability score of the one or more fashion products associated with the user and that have a price greater than a price of the one or more fashion products associated with the user.

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

determining that the user is accessing the website in response to a user selection of a digital advertisement displayed on a different website;

determining one or more fashion products shown in the digital advertisement displayed on the different web site; and

providing the one or more recommendations for the one or more fashion products on the website based upon, at least in part, one or more fashion-ability scores representative of the one or more fashion products shown in the digital advertisement displayed on the different web site and the one or more fashion-ability scores representative of the one or more fashion products on the website.

8. A computer program product comprising a non-transitory computer readable storage medium having a plurality of instructions stored thereon, which, when executed by a processor, cause the processor to perform operations comprising:

training, according to a process, a plurality of neural networks from a plurality of images, wherein each neural network corresponds to an attribute of the plurality of images, a category of the plurality of images, or a sub-category of the plurality of images, wherein the process is selected and identified to process one or more images of a fashion category and/or a fashion sub-category to generate one or more fashion-ability scores each comprising a numerical representation of a corresponding fashion product defined in a corresponding image of the corresponding fashion product;

for each trained neural network, scoring each of the plurality of images against each attribute that the neural network is trained for, and generating one or more scored vectors wherein each scored vector corresponds to a particular attribute used to train the neural network;

joining each of the scored vectors for each of the plurality of images to form a multi-dimensional vector corresponding to a visual representation of each of the plurality of images;

associating, at the computing device, one or more fashion products on a website with a user accessing the website, wherein each of the one or more fashion products associated with the user on the website is assigned a priority score based upon, at least in part a fashion browsing sequence of the user;

generating the one or more fashion-ability scores such that the one or more fashion-ability scores are representative of the one or more fashion products on the website, by selecting an attribute and retrieving the scored vector that is trained for the selected attribute;

in response to retrieving the scored vector trained for the selected attribute, producing the one or more fashion-ability scores that represents one or more fashion products corresponding to the selected attribute; and

providing one or more recommendations to the user for the one or more fashion products on the website based upon, at least in part, one or more fashion-ability scores representative of the one or more fashion products associated with the user on the website and the one or more fashion-ability scores representative of the one or more fashion products on the website, wherein the one or more recommendations are presented to the user in order of the priority score assigned to the one or more fashion products on the website.

9. The computer program product of claim 8 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing one or more recommendations for one or more newly added fashion products based upon, at least in part, the one or more fashion-ability scores representative of the one or more fashion products associated with the user on the website and one or more fashion-ability scores representative of the one or more newly added fashion products.

10. The computer program product of claim 8 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website with a fashion-ability score within a threshold of the fashion-ability score of the one or more fashion products associated with the user.

11. The computer program product of claim 10 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for one or more fashion products on the website from a different fashion category than a fashion category of the one or more fashion products associated with the user.

12. The computer program product of claim 8 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website with a fashion-ability score greater than the fashion-ability score of the one or more fashion products associated with the user.

13. The computer program product of claim 8 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website from the same fashion category as the fashion products associated with the user that have fashion-ability scores within a threshold of the fashion-ability score of the one or more fashion products associated with the user and that have a price greater than a price of the one or more fashion products associated with the user.

14. The computer program product of claim 8 , further comprising:

determining that the user is accessing the website in response to a user selection of a digital advertisement displayed on a different website;

determining one or more fashion products shown in the digital advertisement displayed on the different web site; and

providing the one or more recommendations for the one or more fashion products on the website based upon, at least in part, one or more fashion-ability scores representative of the one or more fashion products shown in the digital advertisement displayed on the different website and the one or more fashion-ability scores representative of the one or more fashion products on the website.

15. A computing system including one or more processors and one or more memories configured to perform operations comprising:

training, according to a process, a plurality of neural networks from a plurality of images, wherein each neural network corresponds to an attribute of the plurality of images, a category of the plurality of images, or a sub-category of the plurality of images, wherein the process is selected and identified to process one or more images of a fashion category and/or a fashion sub-category to generate one or more fashion-ability scores each comprising a numerical representation of a corresponding fashion product defined in a corresponding image of the corresponding fashion product;

for each trained neural network, scoring each of the plurality of images against each attribute that the neural network is trained for, and generating one or more scored vectors wherein each scored vector corresponds to a particular attribute used to train the neural network;

joining each of the scored vectors for each of the plurality of images to form a multi-dimensional vector corresponding to a visual representation of each of the plurality of images;

associating, at the computing device, one or more fashion products on a website with a user accessing the website, wherein each of the one or more fashion products associated with the user on the website is assigned a priority score based upon, at least in part a fashion browsing sequence of the user;

generating the one or more fashion-ability scores such that the one or more fashion-ability scores are representative of the one or more fashion products on the website, by selecting an attribute and retrieving the scored vector that is trained for the selected attribute;

in response to retrieving the scored vector trained for the selected attribute, producing the one or more fashion-ability scores that represents one or more fashion products corresponding to the selected attribute; and

providing one or more recommendations to the user for the one or more fashion products on the website based upon, at least in part, one or more fashion-ability scores representative of the one or more fashion products associated with the user on the website and the one or more fashion-ability scores representative of the one or more fashion products on the website, wherein the one or more recommendations are presented to the user in order of the priority score assigned to the one or more fashion products on the website.

16. The computing system of claim 15 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing one or more recommendations for one or more newly added fashion products based upon, at least in part, the one or more fashion-ability scores representative of the one or more fashion products associated with the user on the website and one or more fashion-ability scores representative of the one or more newly added fashion products.

17. The computing system of claim 15 , wherein providing the one or more recommendations to the user for the one or more fashion products on the web site includes:

providing the one or more recommendations for the one or more fashion products on the website with a fashion-ability score within a threshold of the fashion-ability score of the one or more fashion products associated with the user.

18. The computing system of claim 17 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for one or more fashion products on the website from a different fashion category than a fashion category of the one or more fashion products associated with the user.

19. The computing system of claim 15 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website with a fashion-ability score greater than the fashion-ability score of the one or more fashion products associated with the user.

20. The computing system of claim 15 , wherein providing the one or more recommendations to the user for the one or more fashion products on the website includes:

providing the one or more recommendations for the one or more fashion products on the website from the same fashion category as the fashion products associated with the user that have fashion-ability scores within a threshold of the fashion-ability score of the one or more fashion products associated with the user and that have a price greater than a price of the one or more fashion products associated with the user.