While recommender systems have become an integral component of the Web experience,
their heavy reliance on user data raises privacy and security concerns. Substituting user …

The scarcity of realistic datasets poses a significant challenge in benchmarking
recommender systems and social network analysis methods and techniques. A common …

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 …

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 …

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 …

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 …