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US 12,118,464 B2Granted
Joint embedding content neural networks
AssigneeSnap Inc.
InventorsLawrence Jason Muhlstein, Leonardo Ribas Machado das Neves, Yanen Li, Ning Xu
Life of this patent
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Abstract
A neural network system can select content based on user and item content embeddings in an approach that can be updated in real time on the user device without server support. Requests for content sent to the server can include an anonymous user embedding that includes data describing the user's inputs. The content that is nearest to the user embedding in a joint embedding space can be returned as suggested content.
Claims18
A method performed on a user device, the method comprising:
- generating, using a user embedding neural network, a user embedding with user attribute data as a first input and user interactions as a second input, the user attribute data comprising at least one of:
- a gender of a user, an age of the user, or a geographic location of the user;
- receiving an indication of a user interaction performed on a content item;
- generating, using the user embedding neural network, an updated user embedding based on the user interaction and the content item;
- identifying one or more content items using the updated user embedding and content embeddings, wherein the content embeddings and the updated user embedding share a joint embedding space, and wherein the content embeddings are generated using a content embeddings neural network, wherein the content embeddings neural network comprises two or more content embedding neural networks, the two or more content embedding neural networks corresponding to two or more content types, and wherein the user embedding neural network is trained jointly with the two or more content embedding neural networks;
- and
- storing, on the user device, the identified one or more content items.
4 more elements
A non-transitory machine-readable storage device embodying instructions that, when executed by one or more processors of a user device, cause the one or more processors to perform operations comprising:
- generating, using a user embedding neural network, a user embedding with user attribute data as a first input and user interactions as a second input, the user attribute data comprising at least one of:
- a gender of a user, an age of the user, or a geographic location of the user;
- receiving an indication of a user interaction performed on a content item;
- generating, using the user embedding neural network, an updated user embedding based on the user interaction and the content item;
- identifying one or more content items using the updated user embedding and content embeddings, wherein the content embeddings and the updated user embedding share a joint embedding space, and wherein the content embeddings are generated using a content embeddings neural network, wherein the content embeddings neural network comprises two or more content embedding neural networks, the two or more content embedding neural networks corresponding to two or more content types, and wherein the user embedding neural network is trained jointly with the two or more content embedding neural networks;
- and
- storing, on the user device, the identified one or more content items.
4 more elements
A user device comprising:
- one or more processors;
- and
- a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
- generating, using a user embedding neural network, a user embedding with user attribute data as a first input and user interactions as a second input, the user attribute data comprising at least one of:
- a gender of a user, an age of the user, or a geographic location of the user;
- receiving an indication of a user interaction performed on a content item;
- generating, using the user embedding neural network, an updated user embedding based on the user interaction and the content item;
- identifying one or more content items using the updated user embedding and content embeddings, wherein the content embeddings and the updated user embedding share a joint embedding space, and wherein the content embeddings are generated using a content embeddings neural network, wherein the content embeddings neural network comprises two or more content embedding neural networks, the two or more content embedding neural networks corresponding to two or more content types, and wherein the user embedding neural network is trained jointly with the two or more content embedding neural networks;
- and
- storing, on the user device, the identified one or more content items.
7 more elements
Dependencies are inferred from the claim text.