Generating recommendations using a deep-learning model

• Main Author: Green, Bradley Ray
• Format: Patent
• Language: English
• Published: 14.06.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

In one embodiment, an embedding is determined for each entity in a set of entities that is selected from a plurality of entities. Each embedding corresponds to a point in an embedding space, which includes points corresponding to embeddings of entities. The embeddings of the entities are determined using a deep-learning model. Embeddings are determined for each entity attribute in a set of entity attributes. Each of the entity attributes in the set is of an entity-attribute type and is associated with at least one entity. The entity-attribute embeddings are refined using the deep-learning model. The embeddings of the entities in the set of entities are modified based on the entity-attribute embeddings that are associated with the respective entity to obtain updated embeddings for each entity in the set. The updated embeddings include information regarding the entity attributes that are associated with the respective entities.