Abstract Knowledge Graphs (KG) and associated Knowledge Graph Embedding (KGE)
models have recently begun to be explored in the context of drug discovery and have the …

Leveraging the side information associated with entities (ie, users and items) to enhance
recommendation systems has been widely recognized as an essential modeling dimension …

知识图谱是赋予机器背景知识的大规模语义网络. 利用知识图谱对多源异构的医学信息进行有序
化组织, 能有效提升海量医学资源的利用价值, 推动医学智能化发展. 从知识图谱的关键技术 …

Large language models (LLMs) are widely adopted in knowledge-intensive tasks and have
achieved impressive performance thanks to their knowledge abilities. While LLMs have …

Biomedical knowledge graphs (KGs) hold rich information on entities such as diseases,
drugs, and genes. Predicting missing links in these graphs can boost many important …

Political perspective detection has become an increasingly important task that can help
combat echo chambers and political polarization. Previous approaches generally focus on …

Explainability and Safety engender trust. These require a model to exhibit consistency and
reliability. To achieve these, it is necessary to use and analyze data and knowledge with …

With the advent of pretrained language models (LMs), increasing research efforts have been
focusing on infusing commonsense and domain-specific knowledge to prepare LMs for …

Objective SNOMED CT is the largest clinical terminology worldwide. Quality assurance of
SNOMED CT is of utmost importance to ensure that it provides accurate domain knowledge …

Leveraging the side information associated with entities (ie users and items) to enhance the
performance of recommendation systems has been widely recognized as an important …