Hyper-personalize advertising:Build solutions and workflows to automatically generate web content based on real-time inputs and predefined asset variants. For example, cinematic renders of a product can be generated on demand by an AI from a single dataset, using input data such as region, languag...
This paper introduces a novel approach utilizing the Graph Neural Network (GNN) to enhance demand prediction accuracy by leveraging the spatial relationships inherent in online sales data, named SGNN. Drawing from the rich dataset provided in the fourth Kaggle competition, we construct a ...
Same as Electronics dataset, five labelers label each pair from three labels (“complementary", “substitutable" or “irrelevant"). The consensus results again are generated from majority voting. This results in 299 pairs of product types with consensus labels, including 159 “irrelevant" pairs, ...
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Electronic commerce dataset. The adversarially trained recommender model was developed using a dataset collected from an online retailer (https://www.kaggle.com/retailrocket/ecommerce-dataset). The dataset describes website visitors and their behaviors (view, “add” or buy items available for purchase...