Abstract: Systems and methods directed to returning personalized image-based search results are described. In examples, a query including an image may be received, and a personalized item embedding may be generated based on the image and user profile information associated with a user. Further, a plurality of candidate images may be obtained based on the personalized item embedding. The candidate images may then be ranked according to a predicted level of user engagement for a user, and then diversified to ensure visual diversity among the ranked images. A portion of the diversified images may then be returned in response to an image-based search.

Abstract: Aspects of the present disclosure relate to a providing related content recommendations in response to a user search query by supervising the training of pair embeddings using contrastive learning and pairwise co-click signals. The approach combines a two tower model architecture with a cascaded multilayer perceptron model to enable the adoption of variable combinations of input features and more representative learned pair embeddings. The learned embeddings undergo supervised contrastive loss training to generate a related content recommendation model, which is subsequently evaluated using both online and offline metrics. The related content recommendation model can provide results to search queries that improve recommendation quality and increase user engagement, thereby ultimately enhancing long term user experience.

Abstract: Systems and methods directed to returning personalized image-based search results are described. In examples, a query including an image may be received, and a personalized item embedding may be generated based on the image and user profile information associated with a user. Further, a plurality of candidate images may be obtained based on the personalized item embedding. The candidate images may then be ranked according to a predicted level of user engagement for a user, and then diversified to ensure visual diversity among the ranked images. A portion of the diversified images may then be returned in response to an image-based search.