The scarcity of realistic datasets poses a significant challenge in benchmarking recommender systems and social network analysis methods and techniques. A common …
JMC Velasquez, AS Cochanco… - Journal of Applied …, 2023 - journal.yrpipku.com
The elderly were a member of the vulnerable group which the government supported and assisted in every way possible. To contribute to the support and assistance needed by the …
B Kaabachi, J Despraz, T Meurers, K Otte, M Halilovic… - medRxiv, 2023 - medrxiv.org
Introduction: Sharing and re-using health-related data beyond the scope of its initial collection is essential for accelerating research, developing robust and trustworthy machine …
Recommendation system services have become crucial for users to access personalized goods or services as the global e-commerce market expands. They can increase business …
SK Padinjarekkara, J Alecci, M Popa - ICPRAM, 2024 - scitepress.org
The proposed method XPCA Gen, introduces a novel approach for synthetic tabular data generation by utilising relevant patterns present in the data. This is performed using …
Data governance is crucial in the government sector, emphasising data privacy and ethics. The rise of synthetic data in Data-Centric AI has the potential to address data quantity …
Y Yu, L Jianping, D Weiwei - 2022 19th International Computer …, 2022 - ieeexplore.ieee.org
Deep learning has made remarkable research advancements and wide-ranging applications in the domains of computer vision, multimodal, natural language processing …
A notorious challenge for recommender systems on online platforms is to accurately and fairly recommend items that align with users' preferences while retaining user privacy. These …
The foundations of many recent machine learning successes are natural language representations pretrained over vast amounts of unstructured text. Over the past several …