Using data analytics to properly extracting insights that are in-line to the enterprises strategic
goals is crucial for the business sustainability. Develo** the most fitting context as a …

Enterprise risk management holds significant importance in fostering sustainable growth of
businesses and in serving as a critical element for regulatory bodies to uphold market order …

Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the
collective management of evolving knowledge. The present work aims to provide an …

Abstract Large Language Models (LLMs) exploit fine-tuning as a technique to adapt to
diverse goals, thanks to task-specific training data. Task specificity should go hand in hand …

Global datasphere is increasing fast, and it is expected to reach 175 Zettabytes by 20251.
However, most of the content is unstructured and is not understandable by machines …

As the latest achievement of the development in semiotics, knowledge graph has been
recognized and widely used by more and more researchers for its rich semantic information …

The need for reasoning over temporal data has recently emerged. DatalogMTL is a highly
suitable language to handle many real-world applications. In spite of the deep theoretical …

Automated theorem prover (ATP) for first-order logic (FOL), as a significant inference engine,
is one of the hot research areas in the field of knowledge representation and automated …

As part of cognitive intelligence, concept cognition for knowledge graphs aims to clearly
grasp the typical characteristics of the things referred to by the concept, which can provide …

Deep graph clustering, a fundamental yet formidable task in data analysis, aims to partition
samples belonging to the same category into their respective clusters. Recently, significant …