This paper explores the applications and challenges of graph neural networks (GNNs) in
processing complex graph data brought about by the rapid development of the Internet …

This paper delves into the application of adversarial domain adaptation (ADA) for enhancing
credit risk assessment in financial institutions. It addresses two critical challenges: the cold …

With the rapid development of artificial intelligence technology, especially the increasingly
widespread application of question-and-answer systems, high-quality question generation …

Amidst the swift evolution of social media platforms and e-commerce ecosystems, the
domain of opinion mining has surged as a pivotal area of exploration within natural …

With the explosive growth of Internet data, users are facing the problem of information
overload, which makes it a challenge to efficiently obtain the required resources …

This paper introduces a novel deep-learning method for the automatic detection and
segmentation of lung nodules, aimed at advancing the accuracy of early-stage lung cancer …

This paper explores the importance of credit risk management in the global financial market
environment, especially for the prediction of bond default risk. With the advent of the big data …

This paper proposes a medical literature summary generation method based on the BERT
model to address the challenges brought by the current explosion of medical information. By …

This paper presents a novel approach to credit risk prediction by employing Graph
Convolutional Neural Networks (GCNNs) to assess the creditworthiness of borrowers …

In the current context of accelerated globalization and digitalization, the complexity and
uncertainty of financial markets are increasing, and the identification and prevention of …