Sequential recommender systems often struggle with accurate personalized
recommendations due to data sparsity issues. Existing works use variational autoencoders …

Finance sector loss can be minimized by reducing the number of defaulters who often miss
payments during debt collection. Most research focused on the credit risk analysis before …

Recommender systems play a crucial role in hel** users navigate the vast amount of
information available in the digital age. Traditional recommendation approaches, such as …

In the current digital landscape, both information consumers and producers encounter
numerous challenges, underscoring the importance of recommender systems (RS) as a vital …

Genetic markers for acne are being studied to create personalized treatments based on an
individual's genes, and the field is benefiting from the application of artificial intelligence (AI) …

Students are a gold asset for each country. Proper guidance/recommendation to the
students regarding their education-related issues can ultimately result in uplifting the …

Spectral clustering and matrix factorization are two widely utilized algorithms for community
detection. On the one hand, most existing spectral clustering algorithms focus on learning …

Thermal effects in hypersonic vehicles, such as severe aerodynamic heating, can greatly
influence their thermodynamic behavior. These effects can cause uneven temperature …

A knowledge transfer-based cross-domain recommender system is currently a research
hotspot. Existing research has reached a high level of maturity in mining potential …

Recommendation systems are ubiquitous in various domains, facilitating users in finding
relevant items according to their preferences. Identifying pertinent items that meet their …