Cross-view hypergraph contrastive learning for attribute-aware recommendation

A Ma, Y Yu, C Shi, Z Guo, TS Chua - Information Processing & …, 2024 - Elsevier
Recommender systems typically model user–item interaction data to learn user interests and
preferences. However, user interactions are often sparse and noisy. Moreover, existing …

Enhancing user intent capture in session-based recommendation with attribute patterns

X Liu, Z Li, Y Gao, J Yang, T Cao… - Advances in …, 2023 - proceedings.neurips.cc
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 …

Shop** mmlu: A massive multi-task online shop** benchmark for large language models

Y **, Z Li, C Zhang, T Cao, Y Gao, P Jayarao… - ar** is a complex multi-task, few-shot learning problem with a wide and
evolving range of entities, relations, and tasks. However, existing models and benchmarks …

[HTML][HTML] Behind the Clicks: Can Amazon allocate user attention as it pleases?

R Rock, I Strauss, T O'Reilly, M Mazzucato - Information Economics and …, 2024 - Elsevier
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 …

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 …

Customer Understanding for Recommender Systems

MM Rahman, Y Hirate - Proceedings of the 17th ACM International …, 2024 - dl.acm.org
Recommender systems are powerful tools for enhancing customer engagement and driving
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

C Yu, X Liu, J Maia, Y Li, T Cao, Y Gao… - Companion of the 2024 …, 2024 - dl.acm.org
Applications of large-scale knowledge graphs in the e-commerce platforms can improve
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?

JM Rodriguez, N Tavassoli, E Levy… - … on Information Retrieval, 2024 - Springer
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 …

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 …