公开(公告)号：US20240331003A1

公开(公告)日：2024-10-03

申请号：US18295104

申请日：2023-04-03

Applicant: ADOBE INC.

Inventor： Michele SAAD ,  Robert William BURKE, JR. ,  Irgelkha Mejia ,  Ronald Eduardo ORIBIO

IPC: G06Q30/0601

CPC classification number: G06Q30/0627 ,  G06Q30/0631 ,  G06Q30/0643

Abstract: A search system determines a hierarchy of attributes for a set of search results and returns the search results based on a top-ranked attribute. The search system identifies item listings based on a search input and determines attributes of the item listings. A machine learning model generates a hierarchy of the attributes. The search results are provided based on a top-ranked attribute from the hierarchy of the attributes.

公开(公告)号：US20240095800A1

公开(公告)日：2024-03-21

申请号：US17948997

申请日：2022-09-20

Applicant: ADOBE INC.

Inventor： Ronald Eduardo ORIBIO ,  Robert William BURKE, JR. ,  Michele SAAD ,  Irgelkha MEJIA

IPC: G06Q30/06

CPC classification number: G06Q30/0627 ,  G06Q30/0629 ,  G06Q30/0643

Abstract: A search system employs arrival times with associated confidence scores as search facets for identifying items. The search system identifies a plurality of items based on search input. An arrival time and associated confidence score are determined for each item from the plurality of items. Search results are provided for the plurality of items in response to the search input. The search results are provided based at least in part on the arrival times and associated confidence scores for the plurality of items.

公开(公告)号：US20240420205A1

公开(公告)日：2024-12-19

申请号：US18336815

申请日：2023-06-16

Applicant: ADOBE INC.

Inventor： Soumya UNNIKRISHNAN ,  Michele SAAD ,  Bingxuan LIANG

IPC: G06Q30/0601 ,  G06T11/00

Abstract: Methods and systems are provided for using generative AI to optimize product search queries. In embodiments described herein, product descriptions and product images for a plurality of products are obtained. A multi-modal style classification model classifies each product into a corresponding style of a plurality of styles based on the product's product description and product image. Relationships of each product to other products in the plurality of products are stored in a knowledge graph based on the corresponding style of each product and the corresponding product description of each product. An image is generated by a text-to-image diffusion model with a set of products of the plurality of products based on the relationships of each product of the plurality of products to other products in the plurality of products.

公开(公告)号：US20240330754A1

公开(公告)日：2024-10-03

申请号：US18194501

申请日：2023-03-31

Applicant: ADOBE INC.

Inventor： Soumya UNNIKRISHNAN ,  Saina LAJEVARDI ,  Michele SAAD

IPC: G06N20/00 ,  G06N3/0455 ,  G06Q30/018 ,  G06Q30/0283 ,  G06Q30/0601

CPC classification number: G06N20/00 ,  G06N3/0455 ,  G06Q30/018 ,  G06Q30/0283 ,  G06Q30/0625 ,  G06Q30/0631

Abstract: Methods and systems are provided for using machine learning to efficiently promote eco-friendly products. In embodiments described herein, a product descriptions associated with a product is obtained. The product description includes subject matter indicating an environmental effect of the product. Thereafter, a score for the product correlated to the environmental effect of the product is generated by a machine learning model based on the product description of the product. The score is then provided for presentation to a user to indicate the correlated environmental effect of the product.

公开(公告)号：US20250029171A1

公开(公告)日：2025-01-23

申请号：US18355880

申请日：2023-07-20

Applicant: ADOBE INC.

Inventor： Soumya UNNIKRISHNAN ,  Michele SAAD

IPC: G06Q30/0601

Abstract: Methods and systems are provided for using machine learning to optimize UoM representations. In embodiments described herein, units of measure (UoMs) and relationships of each of UoMs to textual representations of each of the UoMs are stored in a knowledge graph. Text corresponding to a measurement of a product is extracted by an inference model. A recommended textual representation of the measurement of the product by is determined by an autoencoder model including a corresponding textual representation of one of the UoMs from the textual representations of the one of the UoMs stored in the knowledge graph. The recommended textual representation of the measurement of the product is then displayed.

公开(公告)号：US20250014081A1

公开(公告)日：2025-01-09

申请号：US18888379

申请日：2024-09-18

Applicant: Adobe Inc.

Inventor： Michele SAAD ,  Matthew Cecil ZIMMERMAN

IPC: G06Q30/0601 ,  G06F16/22 ,  G06F16/245 ,  G06F16/28 ,  H03M7/30

Abstract: An effective stock keeping unit (SKU) management system encodes catalog data into an embedding per catalog item. An embedding space is created by encoding catalog item data into an embedding per catalog item. The embedding is created by generating an index, where a number of rows represents a number of catalog items and a number of columns represents a number of fields associated with each catalog item. The index is then denormalized using customer groups and transformed by compressing the number of columns, to create the embedding space. In some configuration, a machine learning model is trained using catalog data. In the embedding space, item similarity is encoded by clustering catalog SKUs into groups in the embedding space, by placing similarly related items close to each other in the embedding space. Catalog items are then searched for in the embedding, with the closest clusters searched for a particular catalog item.

公开(公告)号：US20240078583A1

公开(公告)日：2024-03-07

申请号：US17903295

申请日：2022-09-06

Applicant: ADOBE INC.

Inventor： Ronald Eduardo ORIBIO ,  Robert William BURKE, JR. ,  Michele SAAD ,  Irgelkha MEJIA

IPC: G06Q30/06

CPC classification number: G06Q30/0627 ,  G06Q30/0631 ,  G06Q30/0641

Abstract: A search system generates custom attributes for use as search facets. User input associated with an image of a target item available on a listing platform is received. The image is analyzed to determine an attribute of the target item as a custom attribute. A value for the custom attribute is determined for each of a number of other items available on the listing platform that are of the same item type as the target item. Search results are provided based at least in part on the values of the custom attribute for the other items.