Patent ID: 11935106
Assignee: BEIJING WODONG TIANJUN INFORMATION TECHNOLOGY CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A system for determining a target garment matching an inputted garment, wherein the system comprises a computing device, the computing device comprises a processor and a storage device storing computer executable code, and the computer executable code, when executed at the processor, is configured to:
provide an attribute extractor comprising a convolutional neural network (CNN);
train the attribute extractor by using attribute training data, wherein the training comprises:
providing the attribute training data, wherein the attribute training data comprises a plurality of training products, and each training product of the plurality of training products has a text description of the training product, an image of the training product, and an attribute label of the training product;
processing the text description of each of the plurality of training products to obtain a predicted product attribute corresponding to the text description of each of the plurality of training products;
processing, by the CNN, the image of each of the plurality of training products;
converting, by a prediction layer of the CNN, latent vector representations from a CNN result to a predicted product attribute corresponding to the image of each of the plurality of training products; and
training the attribute extractor by using the predicted product attribute corresponding to the text description of each of the plurality of training products, the predicted product attribute corresponding to the image of each of the plurality of training products, and the attribute label of each of the plurality of training products;

receive the inputted garment;
extract, by using the trained attribute extractor, attributes from a text description and an image of the inputted garment to obtain extracted attributes;
query a knowledge graph using the extracted attributes to obtain matched attributes;
retrieve candidate products from a garment pool using the matched attributes;
extract features from the inputted garment and the candidate products;
determine the target garment from the candidate products based on grading scores between the features of the inputted garment and the features of the candidate products; and
push the target garment to a terminal of a user who purchased or reviewed the inputted garment,
wherein the target garment is presented to the user by the terminal of the user,
wherein the knowledge graph comprises nodes corresponding to a type of clothes, a category of clothes, attribute keys comprising sleeve-length, color, pattern, and dress length, values of the attribute keys comprising short-sleeve, red and blue, context keys comprising gender, season and style, values of the context keys comprising woman, summer and casual, a combination of the values of the attribute keys and the type of clothes, and a combination of the values of the attribute keys and the category of clothes,
wherein the knowledge graph comprises edges between the nodes, the edges comprising an “IsA” relationship representing that an attribute of one of the nodes belongs to a category of an attribute of another one of the nodes, a “PartOf” relationship representing that attribution of one of the nodes is part of an attribute of another one of the nodes, and a “Matching_Score” relationship representing compatibility between attribution of two nodes,
wherein matching score values of “Matching_Score” relationships are optimized using one or more garment outfit opinions from key opinion leaders (KOLs), and
wherein a matching score value is a current matching score between a first node and a second node after training using a training outfit, and the current matching score is determined based on a previous matching score between the first node and the second node, a trending index of the first node, and a trending index of the second node.