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Digital research artifacts (articles, datasets, software, etc.) are the basis for scientific research. Due to the continuous growth and complexity (e.g., due to formats) of such artifacts, ensuring their organization and...

RDF has seen increased adoption in recent years, prompting the standardization of the SPARQL query language for RDF, and the development of local and distributed engines for processing SPARQL queries. This survey paper p...

IntroductionRapid advances in digital technology have significantly increased the auditing industry's demand for interdisciplinary talent. However, current digital-intelligent auditing courses in higher education still f...

Abstract Collaborative filtering and neural recommendation models have advanced substantially over the past decade, yet they frequently struggle to capture the fine-grained structure of user preferences and the rich, mul...

Abstract Background Health insurance is essential for providing access to healthcare, particularly for older individuals. Disparities in awareness and understanding among elderly individuals in urban and rural areas may ...

ABSTRACT Background Emergency and public health problems are unavoidable and can strike at any time. In a globalized world where crises are getting more common, more devastating, and have a substantial influence on socie...

Abstract The pre-training molecular representation learning (MRL) has shown considerable potential in computer-aided drug discovery. Recently, many multimodal pre-training MRL methods have been presented, incorporating m...

Organizations have become highly reliant on a range of data sources that span structured, semi-structured, and unstructured data types. These repositories allow large-scale storage for faster ingestion and analytics but ...

Abstract Objective This study aims to evaluate student acceptance of a Smart Learning Platform (SLP) (based on the Chaoxing Learning System™) to deliver a cardiopulmonary physiotherapy curriculum. The SLP leverages AI-...

Abstract Finding interesting phenomena is the core of scientific discovery, but the notion of interestingness is vaguely defined and heavily reliant on manual judgment. We present InterFeat, an integrative pipeline for a...

Water information systems (ISs) are essential for sustainable water management but are often constrained by fragmented, heterogeneous, and rapidly evolving data. Advances in generative artificial intelligence (GenAI), pa...

Abstract Graph Neural Networks have emerged as a powerful paradigm for artificial intelligence driven drug discovery, offering molecular representation learning that surpasses many conventional approaches. Traditional ex...

Abstract Background Long COVID is an infection-associated chronic condition with uncertain evolution, leading to ambiguity in case definitions and various hypotheses about its pathophysiology. Despite this diversity, cau...

Kyle A Kainec,1 Allison Ludwig,2 Megan Boltz,3 John G Oas,3 J. Lynn Caldwell,2 Daniel M Merfeld1,4 1Department of Otolaryngology – Head and Neck Surgery, Ohio State University Wexner Medical Center, Columbus, OH, USA; ...

Materias / palabras clave: graph algorithms, graph databases, graph representation learning, knowledge graphs, knowledge representation, linked data; Science: Mathematics: Instruments and machines: Electronic computers. Computer science