Multi-task learning has been widely applied in computational vision, natural language
processing and other fields, which has achieved well performance. In recent years, a lot of …

Handling conflicting objectives and finding multiple Pareto optimal solutions are two
challenging issues in solving multiobjective optimization problems (MOPs). Inspired by the …

In recent years, knowledge graph technology has been widely applied in various fields such
as intelligent auditing, urban transportation planning, legal research, and financial analysis …

Recent advancements in recommender systems have focused on integrating knowledge
graphs (KGs) to leverage their auxiliary information. The core idea of KG-enhanced …

Multi-scenario and multi-task recommendation can use various feedback behaviors of users
in different scenarios to learn users' preferences and then make recommendations, which …

Multi-domain recommendation (MDR) aims to improve the recommendation performance in
all target domains simultaneously by leveraging rich data from relevant domains. However …

Recently, there has been a surge in recommendations based on heterogeneous information
networks (HINs), attributed to their ability to integrate complex and rich semantics. Despite …

Accurately predicting the highway traffic speed can reduce traffic accidents and transit time,
and it also provides valuable reference data for traffic control in advance. Three essential …

While Knowledge Graphs (KGs) have long been used as valuable sources of structured
knowledge, in recent years, KG embeddings have become a popular way of deriving …

Abstract Knowledge graph, with its rich edge information, has demonstrated its superiority in
improving interpretability and alleviating the cold start problem, and has been widely applied …