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Cross-view hypergraph contrastive learning for attribute-aware recommendation
Recommender systems typically model user–item interaction data to learn user interests and
preferences. However, user interactions are often sparse and noisy. Moreover, existing …
preferences. However, user interactions are often sparse and noisy. Moreover, existing …
Enhancing user intent capture in session-based recommendation with attribute patterns
The goal of session-based recommendation in E-commerce is to predict the next item that
an anonymous user will purchase based on the browsing and purchase history. However …
an anonymous user will purchase based on the browsing and purchase history. However …
[HTML][HTML] Behind the Clicks: Can Amazon allocate user attention as it pleases?
We investigate Amazon's ability to direct user clicks to more visually prominent search
results, even as quality declines with the increasing prevalence of sponsored advertising …
results, even as quality declines with the increasing prevalence of sponsored advertising …
Combating Missed Recalls in E-commerce Search: A CoT-Prompting Testing Approach
S Wu, Y Hu, Y Wang, J Gu, J Meng, L Fan… - … Proceedings of the …, 2024 - dl.acm.org
Search components in e-commerce apps, often complex AI-based systems, are prone to
bugs that can lead to missed recalls—situations where items that should be listed in search …
bugs that can lead to missed recalls—situations where items that should be listed in search …
Customer Understanding for Recommender Systems
Recommender systems are powerful tools for enhancing customer engagement and driving
sales for Rakuten businesses. However, to achieve their full potential, these systems must …
sales for Rakuten businesses. However, to achieve their full potential, these systems must …
COSMO: A large-scale e-commerce common sense knowledge generation and serving system at Amazon
Applications of large-scale knowledge graphs in the e-commerce platforms can improve
shop** experience for their customers. While existing e-commerce knowledge graphs …
shop** experience for their customers. While existing e-commerce knowledge graphs …
Does the Performance of Text-to-Image Retrieval Models Generalize Beyond Captions-as-a-Query?
Text-image retrieval (T2I) refers to the task of recovering all images relevant to a keyword
query. Popular datasets for text-image retrieval, such as Flickr30k, VG, or MS-COCO, utilize …
query. Popular datasets for text-image retrieval, such as Flickr30k, VG, or MS-COCO, utilize …
Transfer Learning for E-commerce Query Product Type Prediction
A Tigunova, T Ricatte, G Eraisha - ar** platforms, such as Amazon, offer services to billions of people worldwide.
Unlike web search or other search engines, product search engines have their unique …
Unlike web search or other search engines, product search engines have their unique …