Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an important component of our daily life, providing personalized suggestions …
have become an important component of our daily life, providing personalized suggestions …
Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component in our daily lives, providing …
have become an indispensable and important component in our daily lives, providing …
Cmclrec: Cross-modal contrastive learning for user cold-start sequential recommendation
Sequential recommendation models generate embeddings for items through the analysis of
historical user-item interactions and utilize the acquired embeddings to predict user …
historical user-item interactions and utilize the acquired embeddings to predict user …
Macro graph neural networks for online billion-scale recommender systems
Predicting Click-Through Rate (CTR) in billion-scale recommender systems poses a long-
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …
Computational technologies for fashion recommendation: A survey
Fashion recommendation is a key research field in computational fashion research and has
attracted considerable interest in the computer vision, multimedia, and information retrieval …
attracted considerable interest in the computer vision, multimedia, and information retrieval …
Siamese neural networks in recommendation
N Serrano, A Bellogín - Neural Computing and Applications, 2023 - Springer
Recommender systems are widely adopted as an increasing research and development
area, since they provide users with diverse and useful information tailored to their needs …
area, since they provide users with diverse and useful information tailored to their needs …
A critical study on data leakage in recommender system offline evaluation
Recommender models are hard to evaluate, particularly under offline setting. In this article,
we provide a comprehensive and critical analysis of the data leakage issue in recommender …
we provide a comprehensive and critical analysis of the data leakage issue in recommender …
Take a fresh look at recommender systems from an evaluation standpoint
A Sun - Proceedings of the 46th International ACM SIGIR …, 2023 - dl.acm.org
Recommendation has become a prominent area of research in the field of Information
Retrieval (IR). Evaluation is also a traditional research topic in this community. Motivated by …
Retrieval (IR). Evaluation is also a traditional research topic in this community. Motivated by …
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-n Recommendation
O Jeunen, I Potapov, A Ustimenko - Proceedings of the 30th ACM …, 2024 - dl.acm.org
Approaches to recommendation are typically evaluated in one of two ways:(1) via a
(simulated) online experiment, often seen as the gold standard, or (2) via some offline …
(simulated) online experiment, often seen as the gold standard, or (2) via some offline …
Amplifying artists' voices: Item provider perspectives on influence and fairness of music streaming platforms
K Dinnissen, C Bauer - Proceedings of the 31st ACM Conference on …, 2023 - dl.acm.org
The majority of music consumption nowadays takes place on music streaming platforms.
Whichever artists, albums, or songs are exposed to consumers on these platforms therefore …
Whichever artists, albums, or songs are exposed to consumers on these platforms therefore …